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Fundamentals of Chinese Military Intelligent Warfare

中國軍事情報戰基礎

現代英語:

[Abstract] Modern warfare is rapidly evolving into information warfare, and the emergence of intelligent warfare is beginning. Intelligent combat systems are becoming the main force form in intelligent warfare, giving rise to new combat styles such as adaptive warfare, cluster attrition warfare, and simultaneous parallel warfare. “Intelligence control” has become a new high ground for control in warfare. In the future, intelligent warfare will exhibit a phased and accelerated evolution. The development of intelligent technology will determine the direction of intelligent warfare, profoundly transforming the contradictory laws of war, and continuously strengthening war ethics and legal regulations. To meet the challenges of intelligent warfare, we must proactively design intelligent warfare, accelerate the development of intelligent equipment, shape intelligent organizational forms, and strengthen intelligent strategic management.

[Keywords] Intelligent warfare, Information warfare, Evolution of form of warfare, Strategic measures

[Chinese Library Classification Number] E0 [Document Identification Code] A

【DOI】10.16619/j.cnki.rmltxsqy.2021.10.002

Guo Ming is the Vice President, Researcher, and Doctoral Supervisor of the Institute of War Studies at the Academy of Military Sciences of the Chinese People’s Liberation Army. His research focuses on military command. His major works include *Tactics of War* (chief editor) and *A Course in Special Operations* (chief editor).

In recent years, driven by a new round of technological, industrial, and military revolutions, the form of warfare is rapidly evolving towards information warfare, and intelligent warfare is on the verge of emerging. As a new form of future warfare, intelligent warfare is not only revolutionizing people’s understanding of war and military affairs, but is also increasingly attracting the attention of countries around the world. Exploring and mastering the characteristics and laws of intelligent warfare and accelerating the development of military intelligence are contemporary challenges for safeguarding the overall strategic situation of the great rejuvenation of the Chinese nation.

A deep understanding of the driving forces behind the evolution of intelligent warfare

The form of war is the historical stage of war, characterized by the technical attributes of the main weapons, and is the manifestation of human society’s mode of production and movement in the military field. [1] Historically, the form of war has undergone several evolutions from cold weapon war, hot weapon war, mechanized war to information warfare, and is currently evolving towards intelligent warfare. This is the result of the combined effects of multiple factors such as politics, economy, military, science and technology, and culture.

The new round of technological revolution is the fundamental driving force behind the evolution of intelligent warfare. Science and technology are the primary productive forces and the core combat power of modern warfare. Major breakthroughs in military technology and landmark developments in dominant weaponry have triggered entirely new changes in military organization, combat methods, and operational theories, leading to a holistic transformation of warfare and the emergence of new forms of conflict. Since the beginning of the 21st century, new technologies characterized by “intelligence, ubiquity, and greenness” have emerged in rapid succession. In particular, artificial intelligence, driven by new technologies and theories such as mobile internet, big data, supercomputing, and brain science, exhibits new characteristics such as deep learning, cross-disciplinary integration, human-machine collaboration, collective intelligence development, and autonomous control. This has triggered a chain of breakthroughs in the military field, significantly changing the way people, weapons, and the ways in which people and weapons, and weapons and weapons, are combined. Various intelligent equipment projects have emerged, including “multi-purpose unmanned tactical transport” ground vehicles, “loyal wingman” drones, “Stingray” shipborne unmanned refueling aircraft, “Sea Hunter” anti-submarine unmanned surface vessels, satellite robots, “cyberspace vehicles,” “adaptive radar countermeasures,” and the “Alpha” beyond-visual-range air combat system. Human-machine hybrid formations, unmanned swarm warfare, and system-based cognitive deception will become possible. Systemic major innovations have emerged in various fields such as combat methods, command and control, organizational structure, logistics support, and military training. Intelligent warfare, which “uses intelligence to control capabilities,” has begun to emerge.

Strategic competition among major powers is the driving force behind the evolution of intelligent warfare. Military affairs are subordinate to politics, and strategy is subordinate to political strategy. Comrade Mao Zedong pointed out that war is “the highest form of struggle used to resolve contradictions between classes, nations, states, and political groups at a certain stage of development.” [2] Strategic competition among major powers and the resulting military demands are key factors driving the evolution of warfare. During World War II, although the armies of Britain, France, Germany, the United States, and the Soviet Union all possessed tanks, aircraft, and radio communication equipment, only Germany successfully implemented “blitzkrieg.” One very important reason was that Germany attempted to use this to break the strategic dilemma of fighting on two fronts. Currently, the world is undergoing profound changes unseen in a century, and the international balance of power is undergoing the most revolutionary changes since modern times, with profound adjustments taking place in the international political and economic landscape. Out of strategic considerations to maintain its world hegemony, the United States proposed the “Third Offset Strategy,” which clearly prioritizes artificial intelligence and autonomy as the technological pillars for development. It accelerates the development of military intelligence from aspects such as war design, operational concept development, technology research and development, and military spending, actively seizing the initiative in the military intelligence revolution and seeking to gain strategic initiative with new technological advantages. Russia insists on investing its limited scientific and technological resources in areas with high strategic value, cutting-edge technology, and great practicality, and regards intelligence as the key to the modernization of weapons and equipment. It has clearly proposed to increase the proportion of unmanned combat systems to 30% by 2025. [3] Other major powers such as Britain, France, India, and Japan are not to be outdone and have increased their investment and deployment in military intelligence. The fierce international strategic competition not only affects the strategic focus of military intelligence development in various countries, but also promotes the evolution and development of intelligent warfare.

Military theoretical innovation is the ideological precursor driving the evolution of intelligent warfare. It plays a significant guiding role in the development of military technology and the evolution of warfare. Human warfare history shows that for cutting-edge technologies and their materialized weaponry to truly achieve combat capability, they must be guided by advanced military theory. There are numerous examples of clinging to existing military theories and missing opportunities to build and utilize new combat capabilities. The US military has always emphasized designing warfare from a technological perspective, using the development of new operational concepts to drive innovation and leaps in defense technology, weaponry, and combat capabilities. The new operational concepts proposed by the US military in recent years all revolve around the top-level operational concept of “cross-domain collaboration.” For example, the US Air Force’s “distributed operations” decouples capabilities through “distribution” and then aggregates them through “collaboration,” thereby constructing a complete operational system. Reflected in force allocation and application, this means a small number of manned aircraft collaborating with a large number of intelligent unmanned aerial vehicles (UAVs) with decomposed functions to form an operational system. In August 2020, the US Defense Advanced Research Projects Agency (DARPA) organized the third human-machine air combat concept demonstration. In the final virtual duel, the artificial intelligence team decisively defeated the human pilot team. Russia has clearly identified military robots as a key direction for the development of military intelligence. In April of this year, Russian media disclosed that its Aerospace Forces’ “Lightning” multi-functional unmanned system has completed group deployment tests and is capable of achieving the Russian military’s “swarm” combat concept attack mission. [4] The core of these combat concepts that already have certain intelligent characteristics is to explore how intelligent warfare can coordinate the use of various military forces through the improvement of “intelligence” to defeat the opponent and achieve a complete victory with cross-domain asymmetric advantages. The formation of intelligent warfare depends on a deep understanding of intelligent technology, keen insight into its military application potential, and a high degree of integration of the art of war with intelligent technology innovation and development of intelligent military theory.

Exploring practical warfare is the primary means of driving the evolution of intelligent warfare. The evolution of warfare is a dynamic process; each form of warfare undergoes a process of quantitative change leading to qualitative change, and gradual change leading to sudden change. Compared to the rise of information warfare, intelligent warfare currently lacks a complete and typical practical example like the Gulf War. However, experiments and practices in intelligent warfare are propelling intelligent warfare from its inception to its nascent stage, and from its early stages to its advanced levels. In 2015, Russia, in the Syrian war, for the first time deployed four tracked Platform-M combat robots and two wheeled Argo combat robots in a structured manner, along with unmanned reconnaissance aircraft and the Andromeda-D automated command system, pioneering ground combat operations primarily based on combat robots. In January 2018, the Russian military, for the first time in the Syrian theater, used anti-intelligent equipment to destroy, jam, and capture 13 incoming drones. In September 2019, more than a dozen drones attacked two Saudi oil facilities, halving their oil production. In the 2020 Nagorno-Karabakh conflict, during the Azerbaijani army’s attack on the Armenian army, unmanned combat platforms exceeded manned platforms for the first time, reaching more than 75%. The number, frequency, and intensity of drone use were all the highest in the history of human warfare. [5] These practical explorations in intelligent warfare will not only promote the application of intelligent equipment on the battlefield to a wider range, a larger number of deployments, and more complex combat scenarios, but will also promote the gradual upgrading of intelligent warfare methods and anti-intelligent warfare methods in the confrontation, thereby accelerating the profound evolution of intelligent warfare.

Accurately grasp the essential characteristics of intelligent warfare

The mechanized era, represented by steam engines and internal combustion engines, greatly expanded human physical capabilities; the information age, represented by the internet and precision-guided systems, achieved an unprecedented leap in human perception; and the rapid development of intelligent technologies, represented by deep learning and autonomous decision-making, is accumulating the material and capability foundation for the intelligent era of “intelligent control of energy.” From a military perspective, the new combat forces composed of intelligent payloads, intelligent platforms, and intelligent systems will give rise to new combat styles such as unmanned swarm warfare, cognitive control warfare, and intelligent algorithm warfare. Seizing “intellectual control” will become a new commanding height in warfare.

Intelligent combat systems have become the primary form of force. The core essence of intelligent combat systems lies in “human command, machine autonomy, and network support,” a key difference from the mechanized and information-based eras. Intelligence is not unmanned; intelligent combat systems are “unmanned platforms, manned systems”—weapons in the foreground, personnel in the background. Intelligence is not about weapons becoming human, but rather the transplantation of human intelligence into weapons, achieving a high degree of integration between humans and weapons. While current artificial intelligence technology is developing rapidly, it is still human-led and human-mediated, essentially reflecting progress in human understanding of intelligence. Regardless of breakthroughs in intelligent technology, humans will remain the initiators, designers, and ultimate decision-makers of warfare. Human operational thinking is materialized into intelligent weapons in the form of rules, algorithms, software, and data. In war, intelligent weapons implement human operational intentions and achieve predetermined operational objectives. Behind the autonomous operation of intelligent weapons remains a contest of human operational methods, command styles, and willpower. Autonomy is the core attribute of military intelligence and the essential characteristic of intelligent combat forces. In other words, weaponry possesses some of the intellectual attributes of humans, enabling it to adapt to the battlefield environment, self-coordinate complex actions, and self-organize force formations under human decision-making and control. Therefore, all the advantages of intelligent combat forces derive from this characteristic of autonomy. Intelligent combat forces also possess speed; as combat operations are increasingly autonomous, the cycle time of “observation-judgment-decision-strike” will be shortened to near-instantaneous response, thus achieving a generational leap in action speed and combat rhythm. Network technology has spurred the iterative development of the Internet, the Internet of Things, and the Internet of Intelligence, forming the foundation for improving mechanization, achieving informatization, and supporting intelligence. The rapid development of new network technologies such as the Internet of Everything and human-machine interaction is leading combat formations towards a hybrid “manned/unmanned” approach, supporting intelligent combat forces through efficient collaborative networks, enabling mission customization, autonomous formation, and flexible collaboration. Once the network environment on which intelligent combat systems heavily rely is disrupted or the links are broken, their combat functions will suffer significant damage or even paralysis. This has prompted countries worldwide to pay close attention to the resilience of intelligent combat systems against interference and attacks.

Autonomous warfare has become the primary mode of combat. With the widespread application of intelligent combat systems to the armed forces and their gradual emergence as the main combat force on the battlefield, autonomous warfare has risen to become the primary mode of combat, profoundly changing combat styles in terms of autonomy, scale, flexibility, and cognition. Based on the current development trend of military intelligence, it can be predicted that the following combat styles will emerge in the future. First, adaptive warfare. This relies on the autonomous learning capabilities of intelligent weapons to react quickly to complex battlefield environments, achieving autonomous judgment, decision-making, and execution of combat actions, maximizing combat effectiveness. Specific applications include “rapid pinpoint warfare,” “intelligent network paralysis warfare,” and “bionic special operations warfare.” The main advantage of this combat style is that it can greatly overcome inherent weaknesses such as human psychological limitations, combat time limitations, and combat mobility limitations, making it particularly suitable for carrying out combat missions deep into enemy-occupied areas, nuclear radiation zones, and other high-risk areas. Simultaneously, leveraging the agility of intelligent weapons, the rapid pace of attack prevents the enemy from organizing an effective response, thus elevating the use of speed to a new level. Second, cluster attrition warfare. This refers to a combat style that primarily utilizes intelligent unmanned swarms, supplemented by a small number of manned combat systems. It mimics the “collective intelligence” exhibited by animal groups in nature, executing combat missions through a group-based autonomous and collaborative model. Specific applications include “swarm” warfare, “fish school” warfare, and “wolf pack” warfare. The main advantage of this style is the use of low-cost, small intelligent weapons to destroy high-value enemy targets through saturation or suicide attacks, transforming numerical superiority into an asymmetric system advantage over traditional large main battle platforms. Thirdly, there is synchronous parallel warfare. This involves decomposing combat functions into multiple heterogeneous small manned and unmanned combat platforms deployed across the entire domain. By establishing a distributed communication network among these platforms, synchronization is achieved in combat time, space, and hierarchy, enabling a systematic approach to completing combat missions. The main advantage of this style is the use of intelligent networks extending to widely distributed intelligent sensors, combat platforms, and individual soldier systems to conduct synchronous and parallel strikes, seizing combat superiority.

“Intelligence dominance” has become the core of warfare. The development of warfare dominance aligns with the evolution of warfare itself. Firepower and mobility are the dominant factors for victory in mechanized warfare, with land, sea, and air dominance becoming the core of the struggle for dominance. Information power is the dominant factor for victory in informationized warfare, with space and information dominance becoming the core of the struggle for dominance. Intelligent superiority is the dominant factor for victory in intelligent warfare, with “intelligence dominance” becoming the core of the struggle for dominance. Intelligent dominance, autonomous energy control, and winning through intelligence will become the fundamental principles of intelligent warfare. The struggle for “intelligence dominance” is essentially a comprehensive contest of “algorithms + data + cognition.” Algorithms are the core of intelligent technology; “algorithms as tactics, software-defined warfare” have become distinctive features of intelligent warfare. The core of algorithm construction is creating abstract models based on problems and selecting different methods to complete the algorithm design according to the target problem. The side with algorithmic advantage can accurately simulate combat scenarios, precisely estimate combat results, and maximize the deduction of optimal combat plans, providing a powerful means to achieve victory before the battle even begins. “Whoever has the most advanced algorithm will gain the upper hand” has become a new law of warfare. Data is a core resource for many disruptive technologies in the era of intelligence. Mastering, analyzing, and competing for data, and applying it to warfare, has become crucial to victory in intelligent warfare. Intelligent weapons possess some human intellectual characteristics, making the cognitive domain a focal point of conflict. Targeting cognitive loops, relying on intelligent technology to limit the enemy’s acquisition of effective information, force them to use incorrect information, delay cognitive speed, induce cognitive patterns, and block cognitive output, can disrupt enemy command and decision-making, undermine their morale, and achieve customizable and controllable application of the ancient war rule of “winning hearts and minds.” In information warfare, the side that loses information control, although its personnel and platforms may not be destroyed, loses smooth communication and cannot form an organic whole. In intelligent warfare, without intelligent advantage, even with information and energy superiority, the loss of human-machine coordination and autonomous decision-making failures will lead to a significant reduction in overall combat effectiveness.

Intelligentization has not changed the essential nature of war. Marshal Ye Jianying pointed out that “war is fought in two ways: first, politics, and second, technology. Politics determines the nature of war, and technology determines the style of war”[6]. Intelligent warfare has not overturned the basic principles of Marxist war theory, but many new developments and changes will occur in its basic scope. On the one hand, the political determinism of intelligent warfare has not changed, and it is still a tool of politics. Politics determines the motivation, purpose and nature of war. Without the purpose of war determined by politics, war becomes blind killing, and war has no soul. In the present era, hegemonism and power politics are still the main sources of war. Ethnic and religious contradictions, energy resource competition, territorial sovereignty and maritime rights disputes will still be the direct causes of war. The widespread use of unmanned autonomous systems has blurred the boundary between war and non-war. The reduction of strategic and military risks may lead to a reduction in the threshold of future wars. In particular, the dual-use nature of intelligent technologies and the widespread adoption of “open source sharing” models such as crowdsourcing, crowdfunding, and maker initiatives have made the acquisition of equipment and technologies increasingly commercialized. This will profoundly change the main actors in warfare in the intelligent era, leading to a more diversified landscape of war actors, primarily non-state actors. On the other hand, the political factors determining victory in intelligent warfare remain unchanged, still determined by the nature of war itself. Wars that promote historical progress and reflect the political goals of the majority of society are just wars; conversely, those that do not are unjust wars. The principle that just wars will inevitably win, and that the people are the foundation of victory, will remain the ironclad rule for victory in the era of intelligent warfare. However, as intelligent technologies give rise to intelligent societies, the role and status of the public in intelligent warfare will be redefined, significantly expanding the breadth and depth of public participation. The public will increasingly become the direct targets of attack, the main body of defense, and a strong support in intelligent warfare. Therefore, it is essential to examine intelligent warfare dialectically and comprehensively, avoiding purely military or technological perspectives, recognizing the “changes” and “unchanging aspects” of intelligent warfare, and thus exploring the path to victory in intelligent warfare.

Scientific prediction of the development trend of intelligent warfare

At present, intelligent warfare is still in its infancy. Predicting the development trend of intelligent warfare is both necessary and challenging. Some scholars have pointed out that although we can roughly judge the future development trends of technologies such as machine learning, industrial robots, and materials science, we cannot accurately predict how these technologies will be combined and what specific impact they will have on future warfare. [7] This requires us to break away from the mindset of starting from individual technologies and focus on understanding the possible development trends of intelligent warfare as a whole.

Intelligent warfare will evolve in stages. With the exponential, combined, and data-driven progress of modern science and technology, as well as the accelerated transformation and application in the military field, the process of weapon and equipment transformation is constantly shortening. In addition, the world is currently in a period of great development, great change, and great adjustment. Regional turmoil and local wars will become the norm, and the exploration of intelligent combat practices will become more frequent. All of these will promote the accelerated development of intelligent warfare. At the same time, due to the limitations of subjective and objective conditions such as the development of intelligent technology, the integration of intelligent forces into the combat system, and the updating of military viewpoints, the evolution of intelligent warfare will show obvious stages. Some scholars have proposed that in order to truly enter intelligent warfare, artificial intelligence technology needs to reach four levels, namely computational intelligence, perceptual intelligence, cognitive intelligence, and human-machine integrated enhanced intelligence. When artificial intelligence technology reaches the second level, intelligent warfare will begin. When it reaches the fourth level, the era of intelligent warfare will be fully opened. [8] Based on this, it can be preliminarily judged that a relatively typical intelligent warfare will appear in the next 15 years or so, and intelligent warfare may become the basic form of warfare in the next 30 years. Practice shows that every change in the military field and every evolution of the form of warfare originates from the rise of new-type combat forces. New-type combat forces, due to their unique and advanced military technologies, possess a “trump card” nature, often disrupting the balance of power on the battlefield and becoming key forces for victory. Once these new-type combat forces are integrated into the combat system and deployed on a large scale in actual warfare, it signifies a fundamental change in the nature of warfare. The true emergence of intelligent warfare will inevitably be the result of the development and expansion of new combat forces such as intelligent unmanned combat platforms and intelligent unmanned combat swarms, integrating them into the existing combat system. This is a gradual and deepening long-term process, and achieving deep integration from initial integration will not be accomplished overnight.

The development of intelligent technology will determine the direction of intelligent warfare. Intelligent technology is a science and technology that comprehensively develops and utilizes cutting-edge technologies such as brain and cognition, biological intersection, advanced computing, big data, and micro-nano technology to study the mechanisms of intelligent behavior and its realization. As the fundamental driving force and material basis for the evolution of intelligent warfare, the development trend, industrial foundation, technological maturity, and depth and breadth of its application in the military field directly determine the future direction of intelligent warfare. In its more than 60 years of development, artificial intelligence technology has experienced three rises and two falls. Currently, the development of artificial intelligence is still in the early stages of statistical learning and may remain in the stage of weak artificial intelligence for a long time. Strong artificial intelligence, which can evolve independently of humans, is difficult to achieve in the short term. The development and breakthroughs of intelligent technology directly determine whether intelligentization is a higher stage of informatization or a stage even higher than informatization. Currently, the driving force of intelligent technology development on intelligent warfare is concentrated in the following aspects: First, intelligent technology empowers existing weapons and equipment. Although current development primarily focuses on dedicated intelligent systems for specific application scenarios, it has already continuously improved the combat effectiveness of traditional main combat platforms such as aircraft carriers and aircraft, gradually evolving from direct human control to the ability to autonomously complete specific combat missions. Secondly, intelligent technology is transforming future combat command models. The integration and transformation of command and control systems by intelligent technology will promote the hybridization of command entities, the flexibility of command structures, and the agility of command models. Competition for adaptive, self-organizing, and self-coordinating command advantages at the operational level will intensify. Thirdly, intelligent technology is updating future combat processes. Intelligent technology will converge and integrate multiple kill chains across land, sea, air, and space combat domains into a cross-domain kill network, fundamentally changing the traditional single-process combat “from sensor to shooter.”

The laws of contradiction in intelligent warfare will undergo profound changes. Applying the laws of contradiction in warfare is a primary means of understanding its laws, and the confrontation between opposing sides is the fundamental contradiction in war. For intelligent warfare, these fundamental contradictions will manifest as competitive relationships such as concealment versus detection, cognition versus deception, network resilience versus network incapacity, attack versus interception, speed of action versus speed of decision-making, winning popular support versus undermining morale, attrition versus effectiveness, and delivery versus denial. With the accelerated development of intelligent technology, these core combat confrontations will become increasingly intense, and the exchange of advantages will become more frequent, thus driving intelligent warfare towards maturity. The confrontation between concealment and detection on the future battlefield will evolve towards greater intelligence, faster response, smaller size, and lower cost. Intelligent technology, as a strategic high ground technology for wielding the “double-edged sword” of information explosion, will intensify the confrontation of enhancing one’s own battlefield situational awareness and misleading, deceiving, and confusing the enemy. Intelligent network information system design and dynamic target defense technologies provide new ideas for network construction in future warfare, while cognitive electromagnetic manipulation and electromagnetic spectrum warfare, and intelligent cyberspace confrontation technologies provide new ways to attack enemy networks. The development of autonomous unmanned systems and smart munitions is expected to optimize attack methods and enhance offensive power in future warfare. The development of autonomous homing weapons and ultra-short-range interception and active protection capabilities will significantly improve the ability to defend against new threats. Autonomous unmanned systems and swarm collaboration technologies will significantly improve operational speed, while intelligent decision-making assistance and swarm intelligence operating systems can greatly improve decision-making speed. The ubiquitous network, social media, and smart terminals are deeply integrated into human life, unprecedentedly increasing the speed, scope, and accuracy of information dissemination. With the emergence of low-cost swarm drones and missiles, future warfare may well overwhelm enemy defenses with low-cost combat platforms, forcing the enemy into a war they cannot defend against or afford.

The ethical and legal regulations governing intelligent warfare will continue to strengthen. Intelligent technology is a double-edged sword; while driving the evolution of warfare towards intelligent warfare, it also brings a series of new ethical issues and legal dilemmas. For example, is it ethical to entrust machines with the power to decide human life and death? When machines possess the power to control human life and death, humanity may not be facing a brighter future, but rather a bottomless abyss of darkness. Another example is who should be held accountable for war crimes committed by intelligent weapons? This may involve the weapons themselves, users, designers, and manufacturers, and a series of resulting dilemmas regarding responsibility and rights. In recent years, the international community has increasingly emphasized the legal regulation of intelligent weapons, conducting international dialogues through international conferences, establishing relevant institutions to study legal regulatory principles, and issuing ethical guidelines for artificial intelligence, among other things. In July 2017, the Chinese government released the “New Generation Artificial Intelligence Development Plan,” proposing at the national strategic level to “initially establish a legal, ethical, and policy system for artificial intelligence” and “ensure the safe, reliable, and controllable development of artificial intelligence.” In April 2019, the European Commission released ethical guidelines for artificial intelligence, proposing seven conditions including transparency, fairness, safety, and human oversight. In October 2019, the U.S. Defense Innovation Board proposed five principles for the application of military artificial intelligence: responsibility, fairness, traceability, reliability, and controllability. Looking to the future, there is an urgent need for the international community to prioritize security and reliability as a key development direction for intelligent technologies. Strategic dialogue is crucial in areas such as the explainability and transparency of military intelligence, preventing the security risks of “instantaneous collapse” of autonomous weapon systems, and the design of new rules of engagement. This dialogue aims to promote the establishment of international rules for the military application of artificial intelligence and jointly address the global challenges that intelligent warfare may bring.

Strategic initiatives to meet the challenges of intelligent warfare

The advent of intelligent warfare may create a new military generation gap, militarily impacting the balance of power between nations and even triggering a new round of great power rise and fall. Intelligent warfare presents both new and unprecedented challenges to national security and a rare strategic opportunity for our military to achieve a leapfrog development. Faced with these opportunities and challenges, there is an urgent need for forward-looking planning, strategic deployment, and comprehensive measures to seize the strategic high ground in future military competition and firmly grasp the strategic initiative in safeguarding national security and winning intelligent warfare.

Proactively design intelligent warfare. First-rate armies design warfare, second-rate armies respond to warfare, and third-rate armies follow warfare. Facing the impending intelligent warfare, we must anticipate and proactively design warfare as early as possible, aiming to transform from following, keeping pace, to leading, and strive to become visionaries and rule-makers of future warfare. First, we must focus on designing intelligent warfare from a technological perspective, enhancing our understanding of cutting-edge technologies, keenly grasping new trends in technological development, and identifying key areas, directions, and technologies that can trigger the evolution of warfare. We must design the initiative of warfare through technological advancement, the flexibility of warfare through technological integration, and the asymmetry of warfare through technological disruption. Second, we must focus on strengthening the development of new intelligent combat concepts, considering the future security threats facing my country and the missions undertaken by our military. Based on the development, application, and impact of military intelligence, we must focus on how to leverage intelligent warfare to overcome the war threats and strategic dilemmas facing my country. Around various strategic directions and new security fields, we must systematically envision the intelligent combat scenarios that may be faced in the future, vigorously promote innovation in intelligent combat theory, and accelerate the construction of an intelligent combat theory system with Chinese characteristics. Third, we should focus on strengthening the demand-driven development of intelligent warfare, focusing on new intelligent warfare styles, systematically describing the required capabilities, systems, and equipment, and using operational needs to drive the development of military intelligence, ensuring that operational needs are implemented in all aspects and throughout the entire process of military intelligence development, and comprehensively improving the combat effectiveness of military intelligence development.

Developing intelligent weaponry and equipment. Intelligent weaponry and equipment are the material foundation of intelligent warfare and an important symbol of an intelligent military. First, we must adhere to system construction. Information warfare is about systems, and intelligent warfare is even more about systems. Currently, intelligent weaponry and equipment, represented by intelligent command and control systems, intelligent drones, intelligent tanks, intelligent missiles, and intelligent landmines, are still in a stage of fragmented development and far from forming a systematic development. How to build an intelligent weaponry and equipment system, especially an intelligent network information system, has become a major strategic issue facing us. Second, we must adhere to a balanced approach of offense and defense. Where there is a spear, there will inevitably be a shield; where there is intelligent weaponry and equipment, there will inevitably be anti-intelligent weaponry and equipment. We must coordinate the development of offensive and defensive intelligent weaponry and equipment. For intelligent weaponry and equipment, once the enemy obtains the source code, it is equivalent to gaining the right to use the weapon. This places new and higher demands on the construction of intelligent weaponry and equipment that combines offense and defense. Third, we must coordinate the integrated development of mechanization, informatization, and intelligence. We must adhere to the principle of supporting intelligence with mechanization and informatization, and driving mechanization and informatization with intelligence. Through the coupling, proportional optimization, and system integration of elements of mechanization, informatization, and intelligence, we can accelerate the transformation, upgrading, and efficiency improvement of intelligent weaponry and equipment construction.

Shaping an intelligent organizational structure. Without the modernization of the military’s organizational structure, there can be no modernization of national defense and the armed forces. The fundamental function of the military’s organizational system is to ensure the effective integration of personnel and equipment, enabling the formation and continuous improvement of the military’s overall combat capability. To win intelligent wars and build an intelligent military, it is essential to establish an intelligent organizational system and construct an intelligent military force system. An intelligent military force system is an organic whole comprised of combat forces with intelligent weapon platforms as its backbone, organized according to human-machine collaboration and machine self-organization collaboration, conducting combat operations under authorized control or supervision by humans, as well as combat support forces providing reconnaissance, intelligence, communication, and algorithm design, and logistics and equipment support forces. Following the principles of “emphasizing coordinated development, focusing on competitive advantages, and promoting system integration,” and centering on expanding the scale and optimizing troop composition, while inheriting the traditional tree-like structure and service branch structure organizational models, a dual organizational system balancing stability and innovation should be established. Efforts should be made to construct a command system with a virtualized center of gravity, explore and innovate new organizational methods such as cross-domain mixed forces and manned/unmanned mixed formations, and strive to achieve the flexible, organic, and efficient operation of the intelligent military force system.

Strengthening Strategic Management of Intelligentization. The evolution of intelligent warfare begins with technology and is perfected through management. To meet the challenges of intelligent warfare and accelerate the development of military intelligence, we must prioritize strategic management, focusing on improving the quality and efficiency of military intelligence development and the operational efficiency of intelligent military systems. From a holistic perspective, we must strengthen overall planning, system design, centralized management, and categorized guidance, forging a path of intensive and efficient intelligent development. Adapting to the rapid response capabilities required by intelligent warfare, we must optimize management systems and mechanisms, adopting networked and autonomous management models. We must improve the planning and implementation of cutting-edge intelligent technology research and development and the transformation and application of scientific and technological achievements, increasing R&D investment and support to ensure that technological innovation remains at the forefront of the times. We must strengthen the construction of a military standard system for artificial intelligence, promptly promulgate relevant laws, regulations, and rules concerning intelligent facilities, intelligent systems, intelligent weaponry, intelligent personnel, and intelligent warfare, and continuously improve key policies and systems supporting the development of military intelligence. Given the ubiquitous and easily disseminated nature of artificial intelligence technology, and the high degree of coupling between national strategic capabilities, social productivity, and military combat effectiveness, we must further optimize the open and integrated layout of intelligentization construction, streamline organizational leadership mechanisms, build a favorable development environment, and promote the organic unity of national prosperity and military strength.

現代國語:

【摘要】現代戰爭正迅速向資訊戰演進,智能戰的興起已然開始。智慧作戰系統正成為智慧戰的主力運動形態,催生出適應性戰爭、集群消耗戰、同步並行戰等新型作戰方式。 「智慧控制」已成為戰爭控制的新制高點。未來,智能戰將呈現階段性、加速演進的趨勢。智慧科技的發展將決定智慧戰的方向,深刻變革戰爭中相互矛盾的規律,並不斷強化戰爭倫理和法律規範。為因應智慧戰的挑戰,必須積極主動地進行智慧戰設計,加速智慧裝備的研發,塑造智慧化的組織形態,並加強智慧化的策略管理。

【關鍵字】智能戰,資訊戰,戰爭形式演變,戰略措施

【中國圖書館分類號】E0 【文獻識別碼】A

【DOI】10.16619/j.cnki.rmltxsqy.2021.10.002

郭明,中國人民解放軍軍事科學學院戰爭研究所副所長、研究員、博士生導師。研究方向為軍事指揮。主要著作包括《戰爭戰術》(編)和《特種作戰教程》(編)。

近年來,在新一輪技術、工業和軍事革命的推動下,戰爭形式正迅速向資訊戰演變,智慧戰即將興起。作為一種新型的未來戰爭形式,智能戰不僅正在革新人們對戰爭和軍事事務的理解,也日益受到世界各國的關注。探索和掌握智慧戰爭的特徵和規律,加速軍事情報發展,是維護中華民族偉大復興整體戰略情勢的當代挑戰。

深入理解智慧戰爭演進的驅動力

戰爭形式是戰爭的歷史階段,以主要武器的技術屬性為特徵,是人類社會在軍事領域的生產和運動方式的體現。 [1] 從歷史上看,戰爭形式經歷了冷戰、熱戰、機械化戰爭、資訊戰等多次演進,目前正朝著智慧戰爭演進。這是政治、經濟、軍事、科技、文化等多種因素共同作用的結果。

新一輪科技革命是智慧戰爭演進的根本驅動力。科技是現代戰爭的主要生產力和核心戰鬥力。軍事技術的重大突破和主導武器裝備的里程碑式發展,引發了軍事組織、作戰方式和作戰理論的徹底變革,導致戰爭的全面轉型和新型衝突形式的出現。自21世紀初以來,以「智慧化、普及化、綠色化」為特徵的新技術層出不窮。特別是人工智慧,在行動互聯網、大數據、超級運算、腦科學等新技術和理論的驅動下,展現出深度學習、跨學科融合、人機協作、集體智慧發展和自主控制等新特徵。這引發了軍事領域的一系列突破,顯著改變了人員、武器以及人員與武器、武器與武器的結合方式。各種智慧裝備計畫相繼湧現,包括「多用途無人戰術運輸」地面車輛、「忠誠僚機」無人機、「魟魚」艦載無人加油機、「海上獵人」反潛無人水面艦艇、衛星機器人、「網路空間車輛」、「自適應雷達對抗」以及「阿爾法」超視距空戰系統。人機混合編隊、無人群聚作戰和基於系統的認知欺騙將成為可能。作戰方式、指揮控制、組織結構、後勤支援、軍事訓練等各領域都出現了系統性的重大創新。 「以情報控制能力」的智慧戰爭開始出現。

大國間的戰略競爭是智慧戰爭演進的驅動力。軍事從屬於政治,戰略從屬於政治戰略。毛澤東同志指出戰爭是「在特定發展階段,為解決階級、民族、國家和政治團體之間矛盾而採取的最高形式的鬥爭」。 [2] 大國間的戰略競爭及其所產生的軍事需求是推動戰爭演變的關鍵因素。二戰期間,儘管英國、法國、德國、美國和蘇聯的軍隊都擁有坦克、飛機和無線電通訊設備,但只有德國成功實施了「閃電戰」。一個非常重要的原因是,德國試圖利用閃電戰來打破兩線作戰的戰略困境。目前,世界正經歷百年未有之大變局,國際力量平衡正經歷近代以來最劇烈的變革,國際政治經濟格局正在發生深刻的調整。出於維護其世界霸權的戰略考量,美國提出了“第三次抵消戰略”,該戰略明確將人工智慧和自主性作為發展的兩大技術支柱。它從戰爭設計、作戰概念發展、技術研發和軍費開支等各方面加速軍事情報的發展,積極在軍事情報革命中搶佔先機,力求憑藉新的技術優勢獲得戰略主動權。俄羅斯堅持將有限的科技資源投入到具有高戰略價值、尖端技術和實用性的領域,並將情報視為武器裝備現代化的關鍵。俄羅斯已明確提出2025年將無人作戰系統的比例提高到30%。 [3] 英國、法國、印度和日本等其他大國也不甘示弱,紛紛加大對軍事情報的投入與部署。激烈的國際戰略競爭不僅影響各國軍事情報發展的戰略重點,也推動智慧戰的演進與發展。

軍事理論創新是推動智慧戰演進的思想先導,在軍事技術發展和戰爭演進中扮演重要的指導角色。人類戰爭史表明,尖端技術及其物質化武器要真正發揮作戰能力,必須以先進的軍事理論為指導。固守現有軍事理論而錯失建構和運用新型作戰能力的案例不勝枚舉。美軍始終強調從技術角度設計戰爭,透過發展新的作戰概念來推動國防技術、武器裝備和作戰能力的創新與飛躍。近年來美軍提出的新作戰概念均圍繞著「跨域協同」這一最高作戰概念。例如,美軍的「分散式作戰」透過「分散式」將各項能力解耦,再透過「協同」將其聚合,從而建構一個完整的作戰系統。這體現在兵力部署和運用上,意味著少量有人駕駛飛機與大量功能分解的智慧無人機協同作戰,形成一個完整的作戰系統。 2020年8月,美國國防高級研究計畫局(DARPA)組織了第三次人機空戰概念展示。在最終的虛擬對決中,人工智慧團隊取得了決定性的勝利。俄羅斯已明確將軍用機器人視為軍事情報發展的關鍵方向。今年4月,俄羅斯媒體揭露,其空天軍「閃電」多功能無人系統已完成集群部署測試,能夠執行俄軍「集群」作戰概念的攻擊任務。 [4] 這些已具備一定智慧特質的作戰概念的核心在於探索如何透過提升「智慧」來協調各軍事力量的運用,從而憑藉跨域非對稱優勢擊敗對手並取得全面勝利。智慧戰的形成依賴於對智慧技術的深刻理解、對其軍事應用潛力的敏銳洞察,以及戰爭藝術與智慧技術創新和智慧軍事理論發展的高度融合。

探索實戰是推動智能戰演進的首要途徑。戰爭的演變是一個動態過程;每一種戰爭形式都會經歷一個從數量變化到質量變化的過程。漸進式變革最終會導致突發式變革。與資訊戰的興起相比,智能戰目前尚缺乏像海灣戰爭那樣完整且典型的實戰案例。然而,智慧戰領域的實驗和實踐正推動智慧戰從萌芽階段發展到雛形階段,再從早期階段邁向高階階段。 2015年,俄羅斯在敘利亞戰爭中首次系統性地部署了四台履帶式「平台-M」戰鬥機器人和兩台輪式「阿爾戈」戰鬥機器人,並配合無人偵察機和「仙女座-D」自動化指揮系統,開創了以戰鬥機器人為主的地面作戰先河。 2018年1月,俄羅斯軍隊首次在敘利亞戰場使用反情報設備,摧毀、幹擾並捕獲了13架來襲無人機。 2019年9月,十幾架無人機襲擊了沙烏地阿拉伯的兩處石油設施,導致其石油產量減半。在2020年納戈爾諾-卡拉巴赫衝突中,阿塞拜疆軍隊進攻亞美尼亞軍隊期間,無人作戰平台的使用率首次超過有人作戰平台,達到75%以上。無人機的使用數量、頻率和強度均創人類戰爭史新高。 [5] 這些在智慧戰領域的實踐探索,不僅將推動智慧裝備在戰場上更廣泛地應用、部署更多種類、應對更複雜的作戰場景,還將促進對抗中智能戰方法和反智能戰方法的逐步升級,從而加速智能戰的深刻演進。

準確掌握智能戰的本質特徵

以蒸汽機和內燃機為代表的機械化時代極大地拓展了人類的體能;以互聯網和精確導引系統為代表的資訊時代,使人類的感知能力實現了前所未有的飛躍;以深度學習和自主決策為代表的智能技術的快速發展,正在為“智能能源控制”的智能時代積累物質和能力基礎。從軍事角度來看,由智慧載荷、智慧平台和智慧系統構成的新型作戰力量將催生無人集群戰、認知控制戰和智慧演算法戰等新型作戰方式。 「智慧控制」將成為戰爭的新制高點。

智慧作戰系統已成為主要作戰形式。智慧作戰系統的核心在於“人指揮、機器自主、網路支援”,這與機械化和資訊時代有著關鍵區別。智慧並非無人化;智慧作戰系統是「無人平台、有人系統」──武器在前,人員在後。智慧並非武器人性化,而是將人類智慧移植到武器中,實現人與武器的高度融合。儘管目前的人工智慧技術發展迅速,但它仍然是由人主導和人類操控的,本質上反映了人類對智慧理解的進步。無論智慧科技如何突破,人類仍將是戰爭的發起者、設計者和最終決策者。人類的作戰思維以規則、演算法、軟體和資料的形式物化為智慧武器。在戰爭中,智慧武器執行人類的作戰意圖並實現預定的作戰目標。智慧武器的自主運作背後,仍是人類作戰方法、指揮風格和意志力的較量。自主性是軍事智慧的核心屬性,也是智慧作戰部隊的本質特徵。換句話說,武器具備人類的部分智慧屬性,使其能夠在人類的決策和控制下適應戰場環境、自主協調複雜行動並自主組織部隊陣型。因此,智慧作戰部隊的所有優勢都源自於自主性這項特質。智慧作戰部隊也具備速度優勢;隨著作戰行動日益自主化,「觀察-判斷-決策-打擊」的周期將縮短至近乎瞬時響應,從而實現行動速度和作戰節奏的代際飛躍。網路技術推動了互聯網、物聯網和智慧互聯網的迭代發展,為提升機械化水平、實現資訊化和支援情報化奠定了基礎。萬物互聯、人機互動等新型網路技術的快速發展正引領作戰編隊向著作為一種混合「有人/無人」模式,智慧作戰系統透過高效的協同網路支援智慧作戰力量,實現任務客製化、自主編隊和靈活協同。一旦智慧作戰系統高度依賴的網路環境遭到破壞或連結中斷,其作戰功能將遭受重大損害甚至癱瘓。這促使世界各國高度重視智慧作戰系統抵禦幹擾和攻擊的能力。

自主作戰已成為主要作戰模式。隨著智慧作戰系統在軍隊中的廣泛應用及其逐漸成為戰場主力,自主作戰已成為主要作戰模式,從自主性、規模、靈活性和認知等方面深刻改變了作戰方式。基於當前軍事智慧的發展趨勢,可以預測未來將出現以下幾種作戰模式。首先是自適應作戰。這種作戰模式依賴智慧武器的自主學習能力,快速回應複雜的戰場環境,實現自主判斷、決策和作戰行動執行,以最大限度地提高作戰效能。具體應用包括「快速精確打擊」、「智慧網路癱瘓戰」和「仿生特種作戰」。這種作戰方式的主要優勢在於能夠大幅克服人類心理、作戰時間、作戰機動性等方面的固有弱點,使其特別適用於深入敵佔區、核輻射區等高風險區域執行作戰任務。同時,憑藉著智慧武器的敏捷性,快速的攻擊節奏能夠阻止敵人組織有效的應對措施,從而將速度的運用提升到一個新的水平。其次是集群消耗戰。這種作戰方式主要利用智慧無人集群,輔以少量有人作戰系統。它模仿自然界動物群體所展現的“集體智慧”,透過基於群體的自主協作模式執行作戰任務。具體應用包括「蜂群戰」、「魚群戰」和「狼群戰」。這種作戰方式的主要優勢在於利用低成本、小型智慧武器,透過飽和攻擊或自殺式攻擊摧毀高價值敵方目標,從而將數量優勢轉化為對傳統大型主戰平台的不對稱系統優勢。第三種是同步並行作戰。這種作戰方式將作戰功能分解為部署在整個作戰域的多個異質小型有人和無人作戰平台。透過在這些平台之間建立分散式通訊網絡,實現作戰在時間、空間和層級上的同步,從而能夠系統地完成作戰任務。這種作戰方式的主要優點在於利用智慧網絡,將智慧感測器、作戰平台和單兵系統廣泛分佈,進行同步並行打擊,奪取作戰優勢。

「情報優勢」已成為戰爭的核心。戰爭優勢的發展與戰爭本身的演變一致。火力和機動性是機械化戰爭中取得勝利的關鍵因素,陸海空優勢成為爭奪優勢的核心。資訊力量是資訊化戰爭中致勝的關鍵因素,空間和資訊優勢成為爭奪主導權的核心。智慧優勢是智慧戰爭中致勝的關鍵因素,「智能主導」成為爭奪主導權的核心。智慧主導、自主能源控制和以智慧取勝將成為智慧戰爭的基本原則。 「智能主導」的爭奪本質上是「演算法+資料+認知」的綜合較量。演算法是智慧技術的核心;「演算法即戰術,軟體定義戰爭」已成為智慧戰爭的顯著特徵。演算法建構的核心是基於問題創建抽像模型,並根據目標問題選擇不同的方法完成演算法設計。擁有演算法優勢的一方可以精確模擬作戰場景,準確評估作戰結果,並最大限度地推導出最優作戰方案,從而在戰鬥開始前就擁有製勝的強大手段。 「誰擁有最先進的演算法誰就佔優勢」已成為新的戰爭法則。在智慧時代,數據是許多顛覆性技術的核心資源。在智慧戰爭中,掌握、分析和爭奪數據並將其應用於戰爭,已成為取得勝利的關鍵。智慧武器具​​備某些人類智力特徵,使得認知領域成為衝突的焦點。透過智慧技術,針對認知迴路,限制敵方獲取有效訊息,迫使其使用錯誤訊息,延緩其認知速度,誘導其認知模式,並阻斷其認知輸出,可以擾亂敵方的指揮和決策,打擊其士氣,從而實現對「贏得民心」這一古老戰爭法則的可定制化和可控應用。在資訊戰中,失去資訊控制的一方,即使其人員和平台可能未被摧毀,也會失去順暢的溝通,無法形成一個有機的整體。在智慧戰爭中,即使擁有資訊和能源優勢,如果沒有智慧優勢,人機協調的喪失和自主決策的失敗也會導致整體作戰效能的顯著下降。

智能化並未改變戰爭的本質。葉劍英元帥指出,「戰爭有兩種方式:一是政治,二是技術。政治決定戰爭的本質,技術決定戰爭的方式」[6]。智慧戰爭並未顛覆馬克思主義戰爭理論的基本原則,但其基本範圍將出現許多新的發展和變化。一方面,智慧戰爭的政治決定性並未改變,它仍是政治的工具。政治決定戰爭的動機、目的和本質。如果戰爭的目的沒有政治的確定,戰爭就變成了盲目的殺戮,戰爭失去了靈魂。在當今時代,霸權主義和強權政治仍然是戰爭的主要根源。民族和宗教矛盾、能源資源競爭、領土主權和海洋權益爭端仍將是戰爭的直接原因。無人自主系統的廣泛應用模糊了戰爭與非戰爭的界線。戰略和軍事風險的降低可能導致未來戰爭門檻的降低。尤其值得注意的是,智慧科技的雙重用途特性以及眾包、眾籌、創客計畫等「開源共享」模式的廣泛應用,使得裝備和技術的獲取日益商業化。這將深刻改變智慧時代戰爭的主要參與者,導致戰爭行為體更加多元化,其中非國家行為者特別突出。另一方面,決定智慧戰爭勝負的政治因素依然不變,仍取決於戰爭本身的本質。促進歷史進步並反映社會大多數人政治目標的戰爭是正義戰爭;反之,則為非正義戰爭。正義戰爭必勝、人民是勝利基石的原則,仍將是智慧戰爭時代勝利的鐵律。然而,隨著智慧科技催生智慧社會,公眾在智慧戰爭中的角色和地位將被重新定義,公眾參與的廣度和深度將顯著提升。公眾將日益成為攻擊的直接目標、防禦的主力軍以及智慧戰爭的強大後盾。因此,必須辯證、全面地審視智能戰,避免純粹的軍事或技術視角,認識到智能戰的“變化”與“不變”,從而探索智能戰的製勝之道。

智慧戰發展趨勢的科學預測

目前,智能戰仍處於起步階段。預測智能戰的發展趨勢既必要又具有挑戰性。一些學者指出,雖然我們可以大致判斷機器學習、工業機器人、材料科學等技術的未來發展趨勢,但我們無法準確預測這些技術將如何融合,以及它們將對未來戰爭產生何種具體影響。 [7] 這就要求我們摒棄從單一技術出發的思維模式,並著眼於理解智能戰整體可能的發展趨勢。

智能戰將分階段演進。隨著現代科技呈指數級、整合式和數據驅動式發展,以及在軍事領域的加速轉型應用,武器裝備的轉型升級進程也不斷縮短。此外,世界目前正處於大發展、大變革和大調整時期。區域動盪和局部戰爭將成為常態,情報探索也將日益頻繁。智慧作戰實踐將日益頻繁,所有這些都將促進智慧戰爭的加速發展。同時,由於智慧科技發展、智慧力量融入作戰體系、軍事觀點更新等主客觀條件的限制,智慧戰爭的演進將呈現明顯的階段性。一些學者提出,要真正進入智慧戰爭階段,人工智慧技術需要達到四個層次,即計算智能、感知智能、認知智能和人機融合增強智能。當人工智慧技術達到第二層次時,智慧戰爭將開始;當達到第四層次時,智慧戰爭時代將全面開啟。 [8] 基於此,可以初步判斷,未來15年左右將出現較為典型的智慧戰爭,未來30年內智能戰爭可能成為戰爭的基本形式。實踐表明,軍事領域的每一次變革和戰爭形式的每一次演進都源於新型作戰力量的出現。新型作戰力量憑藉著獨特而先進的軍事技術,具有「王牌」性質,往往能夠打破戰場上的力量平衡,成為決定勝負的關鍵力量。一旦這些新型作戰力量融入作戰體系並在實戰中大規模部署,就標誌著戰爭性質的根本性轉變。智慧戰爭的真正出現,必然是智慧無人作戰平台、智慧無人作戰集群等新型作戰力量發展壯大並融入現有作戰體系的結果。這是一個循序漸進、不斷深化的長期過程,從初步融合到深度融合並非一朝一夕之功。

智慧技術的發展將決定智慧戰爭的方向。智慧技術是一門綜合發展與運用腦與認知、生物交叉、先進計算、大數據、微納技術等尖端技術,研究智慧行為機制及其實現方式的科學技術。作為智慧戰爭演進的根本驅動力和物質基礎,人工智慧的發展趨勢、產業基礎、技術成熟度以及在軍事領域的應用深度和廣度直接決定智慧戰爭的未來發展方向。人工智慧技術在60多年的發展歷程中經歷了三次崛起和兩次衰落。目前,人工智慧的發展仍處於統計學習的早期階段,並且可能在很長一段時間內都停留在弱人工智慧階段。能夠獨立於人類演進的強人工智慧,短期內難以實現。智慧科技的發展與突破直接決定智慧化是資訊化的更高階段,還是超越資訊化的更高階段。目前,智慧科技發展對智慧戰爭的驅動力主要集中在以下幾個面向:首先,智慧科技賦能現有武器裝備。雖然目前發展主要集中於針對特定應用場景的專用智慧系統,但它已經不斷提升了航空母艦、飛機等傳統主戰平台的作戰效能,逐步從直接由人類操控發展到能夠自主完成特定作戰任務。其次,智慧技術正在改變未來的作戰指揮模式。智慧技術對指揮控制系統的整合與改造將促進指揮實體的混合化、指揮結構的彈性與指揮模式的敏捷性。作戰層面上對適應性、自組織性和自協調性指揮優勢的競爭將更加激烈。第三,智慧科技正在更新未來的作戰流程。智慧技術將陸、海、空、天等多個作戰領域的多條殺傷鏈融合整合為跨域殺傷網絡,從根本上改變傳統的「從感測器到射手」的單一作戰流程。

智慧戰爭中的矛盾規律將會發生深刻變化。運用戰爭中的矛盾規律是理解戰爭規律的主要途徑,而交戰雙方的對抗是戰爭的根本矛盾。對於智慧戰爭而言,這些根本矛盾將表現為競爭關係。諸如隱藏與偵測、認知與欺騙、網路韌性與網路癱瘓、攻擊與攔截、行動速度與決策速度、贏得民眾支持與打擊士氣、消耗戰與實效、投送與拒止等核心對抗手段,隨著智慧科技的加速發展,這些核心對抗將愈發激烈,優勢交換也將更加頻繁,從而推動智慧戰爭走向成熟。未來戰場上隱蔽與偵測的對抗將朝著更高智慧化、更快反應速度、更小規模和更低成本的方向發展。智慧技術作為運用資訊爆炸這把「雙面刃」的戰略制高點技術,將加劇提升自身戰場態勢感知能力與誤導、欺騙、迷惑敵方之間的對抗。智慧網路資訊系統設計和動態目標防禦技術為未來戰爭中的網路建設提供了新的思路,而認知電磁操控、電磁頻譜戰以及智慧網路空間對抗技術則為攻擊敵方網路提供了新的途徑。自主無人系統和智慧彈藥的發展有望優化未來戰爭的攻擊方式,並增強進攻能力。自主導引武器、超短程攔截和主動防護能力的提升將顯著增強防禦新型威脅的能力。自主無人系統和叢集協同技術將顯著提升作戰速度,而智慧決策輔助和叢集智慧作業系統則能大幅提升決策速度。無所不在的網路、社群媒體和智慧終端已深度融入人類生活,以前所未有的速度、範圍和準確性提升了資訊傳播。隨著低成本集群無人機和飛彈的出現,未來戰爭很可能憑藉低成本作戰平台壓倒敵方防禦,迫使敵方陷入一場既無力抵抗也無法承擔的戰爭。

有關智慧戰爭的倫理和法律規範將不斷完善。智慧科技是一把雙面刃;在推動戰爭向智慧戰爭演進的同時,也帶來了一系列新的倫理問題和法律困境。例如,將決定人類生死的權力賦予機器是否合乎倫理?當機器擁有掌控人類生死的權力時,人類面臨的可能並非更光明的未來,而是無底的黑暗深淵。另一個例子是,誰應該為智慧武器所犯下的戰爭罪行負責?這可能涉及武器本身、使用者、設計者和製造商,以及由此產生的一系列關於責任和權利的難題。近年來,國際社會日益重視智慧武器的法律監管,透過國際會議進行國際對話,建立相關機構研究法律監管原則,並發佈人工智慧倫理準則等。 2017年7月,中國政府發布了《新一代人工智慧發展規劃》,在國家戰略層面提出“初步建立人工智慧的法律、倫理和政策體系”,並“確保人工智慧安全、可靠、可控發展”。 2019年4月,歐盟委員會發布了人工智慧倫理準則,提出了包括透明度、公平性、安全性和人工監督在內的七項條件。同年10月,美國國防創新委員會提出了軍事人工智慧應用的五個原則:責任性、公平性、可追溯性、可靠性和可控制性。展望未來,國際社會迫切需要將安全性和可靠性作為智慧技術發展的關鍵方向。在軍事情報的可解釋性和透明度、防止自主武器系統「瞬間崩潰」帶來的安全風險以及製定新的交戰規則等領域,戰略對話至關重要。此次對話旨在促進制定人工智慧軍事應用的國際規則,並共同應對智慧戰爭可能帶來的全球性挑戰。

因應智慧戰爭挑戰的戰略舉措

智慧戰爭的出現可能會造成新的軍事世代差距,對國家間的軍事力量平衡產生影響,甚至引發新一輪的大國興衰。智慧戰爭既為國家安全帶來了前所未有的新挑戰,也為我軍實現跨越式發展提供了難得的戰略機會。面對這些機會和挑戰,亟需進行前瞻性規劃、戰略部署和綜合措施,在未來的軍事競爭中佔據戰略制高點,牢牢掌握維護國家安全和贏得智慧戰爭的戰略主動權。

主動設計智慧戰爭。一流軍隊設計戰爭,二流軍隊應對戰爭,三流軍隊跟隨戰爭。面對即將到來的智慧戰爭,我們必須儘早預判並主動設計戰爭,力爭從跟隨、並駕齊驅轉變為引領,努力成為未來戰爭的先行者和規則制定者。首先,我們必須從技術角度出發,著力設計智慧戰爭,加深對尖端技術的理解,敏銳掌握技術發展的新趨勢,辨識能夠引發戰爭演進的關鍵領域、方向和技術。我們必須透過科技進步來設計戰爭的主動性,透過科技融合來設計戰爭的彈性,透過科技顛覆來設計戰爭的非對稱性。其次,我們必須著重加強新型智慧作戰概念的研發,結合我國未來面臨的安全威脅和軍隊的任務,在軍事情報發展、應用和影響的基礎上,重點研究如何利用智慧作戰來應對我國面臨的戰爭威脅和戰略困境。圍繞著不同的戰略方向和新的安全領域,我們必須有系統地構想未來可能面臨的智慧作戰場景,大力推動智慧作戰理論創新,加速建構具有中國特色的智慧作戰理論體系。第三,我們應該著重加強智慧作戰需求驅動型發展,聚焦新型智慧作戰模式,系統地描述所需的能力、系統和裝備,以作戰需求為導向,推動軍事情報發展,確保作戰需求在軍事情報發展的各個面向和整個過程中得到貫徹落實,全面提升軍事情報發展的作戰效能。

研發智慧武器裝備。智慧武器裝備是智慧戰爭的物質基礎,也是智慧軍隊的重要像徵。首先,必須堅持系統化建設。資訊戰的核心在於系統,而智慧戰爭更是如此。目前,以智慧指揮控制系統、智慧無人機、智慧坦克、智慧飛彈、智慧地雷等為代表的智慧武器裝備仍處於分散發展階段,距離系統化發展還很遠。如何建構智慧武器裝備系統,特別是智慧網路資訊系統,已成為我們面臨的重大戰略問題。其次,必須堅持攻守平衡發展。有矛必有盾,有智慧武器裝備必有反智能武器裝備。必須協調發展攻防兼備的智慧武器裝備。對於智慧武器裝備而言,一旦敵方取得了原始碼,就相當於獲得了使用該武器的權利。這就對攻防兼備的智慧武器裝備建設提出了新的更高要求。第三,要協調機械化、資訊化和智慧化的一體化發展。要堅持以機械化和資訊化支撐智能化,以智慧化驅動機械化和資訊化的原則。透過機械化、資訊化和智慧化各要素的耦合、比例優化和系統集成,可以加速智慧武器裝備建設的轉型升級和效率提升。

建構智能化的組織結構。沒有軍隊組織結構的現代化,就沒有國防和軍隊的現代化。軍隊組織體系的根本功能是確保人員和裝備的有效整合,從而形成和不斷提升軍隊的整體作戰能力。打贏智慧戰爭,建構智慧化的軍隊。對於精銳軍隊而言,建立智慧組織體系、建構智慧化軍事力量體系至關重要。智慧化軍事力量體係是一個有機整體,由以智慧武器平台為骨幹的作戰力量、按照人機協同和機器自組織協同原則組織起來的作戰力量、在人類授權控製或監督下開展作戰行動的作戰支援力量以及提供偵察、情報、通信和演算法設計的作戰支援力量和後勤裝備支援力量組成。應遵循「強調協同發展、聚焦競爭優勢、推進系統整合」的原則,以擴大規模、優化部隊構成為核心,在繼承傳統樹狀結構和兵種結構組織模式的基礎上,建構穩中創新並重的雙軌組織體系。應努力建構重心虛擬化的指揮體系,探索創新跨域混合部隊、有人/無人混合編隊等新型組織方式,力求實現智慧化軍事力量體系的靈活、有機、高效運作。

加強智能化策略管理。智能戰的演進始於技術,終於管理。為因應智慧戰的挑戰,加速軍事情報發展,必須優先發展戰略管理,並專注於提升軍事情報發展的品質和效率,以及智慧軍事系統的作戰效能。若要從整體加強統籌規劃、系統設計、集中管理和分類指導,打造密集、高效的智慧發展道路。要適應智慧戰對快速反應能力的要求,優化管理體系和機制,採用網路化、自主化的管理模式。要完善前沿智慧技術研發與科技成果轉換應用的規劃與實施,加大研發投入與支持力度,確保技術創新始終處於時代前沿。要加強人工智慧軍事標準體系建設,及時頒布智慧設施、智慧系統、智慧武器、智慧人員和智慧戰的法律法規,不斷完善支持軍事情報發展的關鍵政策和製度。鑑於人工智慧技術的普及性和易傳播性,以及國家戰略能力、社會生產力和軍事作戰效能之間的高度耦合性,我們必須進一步優化智能化建設的開放一體化佈局,精簡組織領導機制,營造良好的發展環境,促進國家繁榮與軍事實力的有機統一。

注释

[1]《中国军事百科全书·战略》(第二版),北京:中国大百科全书出版社,2014年,第506页。

[2]《毛泽东选集》第1卷,北京:人民出版社,1991年,第171页。

[3]赵林:《从空中、地面到水下无人作战系统——无人作战,俄军走了多远》,《解放军报》,2019年1月31日第11版。

[4]陈梓毅、饶雨峰、马建光:《“闪电”无人机或成俄空天军未来作战新秀》,2020年4月16日,人民网,http://military.people.com.cn/n1/2021/0416/c1011-32079848.html。

[5]兰顺正:《纳卡冲突中的现代武器及战术比拼》,《世界知识》,2020年第24期。

[6]《叶剑英军事文选》,北京:解放军出版社,1996年,第250页。

[7]傅莹:《看世界2》,北京:中信出版社,2021年,第292页。

[8]李始江、杨子明、陈分有:《以新理念迎接智能化战争挑战》,《解放军报》,2018年7月26日,第7版。

2021-08-11 15:xx 来源: 《人民论坛·学术前沿》2021年5月下 作者: 郭明

中國原創軍事資源:https://www.rmlt.com.cn/2021/0811/68281848089.shtml

A Look at Chinese Intelligent Warfare: Reflections on Warfare Brought by AGI

檢視中國智能戰:對通用人工智慧帶來的戰爭的反思

現代英語:

AGI and its implications for warfare

  Editor’s Note

  Technology and war are inextricably intertwined. While technological innovation continuously alters the face of warfare, it hasn’t changed the violent nature and coercive purpose of war. In recent years, with the rapid development and application of artificial intelligence (AI) technology, the debate about its impact on warfare has never ceased. Compared to artificial intelligence (AI), artificial general intelligence (AGI) possesses a higher level of intelligence and is considered a form of intelligence comparable to human intelligence. How will the emergence of AGI affect warfare? Will it change the violent and coercive nature of war? This article will explore this question with a series of reflections.

  Is AGI merely an enabling technology?

  Many believe that while large-scale models and generative artificial intelligence demonstrate the powerful military application potential of AGI, they are ultimately just enabling technologies. They can only enhance and optimize weapons and equipment, making existing equipment smarter and improving combat efficiency, but they are unlikely to bring about a true military revolution. Just as “cyber warfare weapons” were once highly anticipated by many countries when they first appeared, but now it seems that these expectations were somewhat exaggerated.

  The disruptive nature of AGI is entirely different. It brings profound changes to the battlefield with reaction speeds and knowledge far exceeding those of humans. More importantly, it fosters rapid technological advancement, resulting in massive disruptive outcomes. On the future battlefield, autonomous weapons will be endowed with advanced intelligence by AGI, their performance will be universally enhanced, and they will become “strong in offense and difficult in defense” due to their speed and swarm advantages. At that time, the highly intelligent autonomous weapons predicted by some scientists will become a reality, with AGI playing a crucial role. Currently, the military applications of artificial intelligence include autonomous weapons, intelligence analysis, intelligent decision-making, intelligent training, and intelligent support, applications that are difficult to summarize simply as “empowerment.” Moreover, AGI develops rapidly, with short iteration cycles, and is constantly evolving. Future warfare requires prioritizing AGI and paying close attention to its potential changes.

  Will AGI make wars disappear?

  Historian Jeffrey Blainey argues that “wars always occur because of misjudgments of each other’s strength or will,” and that with the application of AGI in the military field, misjudgments will become increasingly rare. Therefore, some scholars speculate that wars will decrease or even disappear. Indeed, relying on AGI can significantly reduce misjudgments, but even so, it’s impossible to eliminate all uncertainty, as uncertainty is a defining characteristic of war. Moreover, not all wars arise from misjudgments, and the inherent unpredictability and unexplainability of AGI, along with the lack of experience in using AGI, will introduce new uncertainties, plunging people into an even deeper “fog of artificial intelligence.”

  AGI algorithms also present rational challenges. Some scholars believe that AGI’s ability to mine and accurately predict crucial intelligence has a dual impact. In practice, AGI does indeed make fewer mistakes than humans, improving intelligence accuracy and reducing misjudgments; however, it can sometimes lead to overconfidence and encourage reckless actions. The offensive advantage brought by AGI results in the optimal defensive strategy being “preemptive strike,” disrupting the balance between offense and defense, triggering a new security dilemma, and ultimately increasing the risk of war.

  AGI (Automatic Generative Technology) is highly versatile and easily integrated into weaponry. Unlike nuclear, biological, and chemical technologies, it has a low barrier to entry and is particularly prone to proliferation. Due to technological gaps between countries, immature AGI weapons could potentially be deployed on the battlefield, posing significant risks. For example, the application of drones in recent local wars has spurred many small and medium-sized countries to begin large-scale drone procurement. The low-cost equipment and technologies offered by AGI could very well trigger a new arms race.

  Will AGI be the ultimate deterrent?

  Deterrence is maintaining a capability to intimidate an adversary from taking actions that exceed one’s own interests. Ultimate deterrence is when it becomes so powerful as to be unusable, such as nuclear deterrence that ensures mutual destruction. But ultimately, however, it is “human nature” that determines the outcome—a crucial element that will never be absent from war.

  Without the considerations of “humanity,” will AGI become a formidable deterrent? AGI is fast but lacks empathy; its execution is resolute, severely compressing the space for strategic maneuvering. AGI is a key factor on the future battlefield, but due to a lack of practical experience, accurate assessment is difficult, easily leading to overestimation of the opponent’s capabilities. Furthermore, regarding autonomous weapon control, whether to have humans on-site, providing full supervision, or to have humans off-site, completely relinquishing control, undoubtedly requires careful consideration. Can the firing control of intelligent weapons be handed over to AGI? If not, the deterrent effect will be greatly diminished; if so, can human life and death truly be decided by machines unrelated to them? Research at Cornell University shows that large-scale wargaming models frequently escalate wars with a “sudden nuclear attack,” even when in a neutral state.

  Perhaps one day in the future, AGI will surpass human capabilities, rendering us unable to regulate and control it. Jeffrey Hinton, who coined the term “deep learning,” says he has never seen a case where something with a higher level of intelligence was controlled by something with a lower level of intelligence. Some research teams believe that humans may not be able to supervise super-intelligent AI. Faced with powerful AGI in the future, will we truly be able to control them? This is a question worth pondering.

  Will AGI change the nature of warfare?

  With the widespread use of AGI, will battlefields filled with violence and bloodshed disappear? Some argue that AI warfare far exceeds human capabilities, potentially pushing humanity out of the fray. When AI transforms warfare into a conflict entirely between autonomous robots, will it still be a “violent and bloody war”? When adversaries with unequal capabilities clash, the weaker party may not even have a chance to act. Can war be ended before it even begins through war games? Will AGI fundamentally alter the nature of warfare? Is a “war” without human intervention still a war?

  Yuval Noah Harari, author of *Sapiens: A Brief History of Humankind*, states that all human behavior is mediated by language and influences our history. The Large Language Model (AGI) is a typical example of AGI, differing from other inventions in its ability to create entirely new ideas and cultures. “Artificial intelligence that can tell stories will change the course of human history.” When AGI gains control over language, the entire system of civilization built by humanity could be overturned, without even requiring AGI to develop consciousness. Like Plato’s Allegory of the Cave, will humanity worship AGI as a new “god”?

  AGI (Artificial Intelligence Generative Devices) establishes a close relationship with humans through human language and alters their perceptions, making them difficult to discern and identify. This poses a risk that the will to fight could be controlled by those with ulterior motives. Harari stated that computers don’t need to deploy killer robots; if necessary, they will allow humans to pull the trigger themselves. AGI precisely manufactures and refines situational information, controlling battlefield perception through deepfakes. This can be achieved through drones faking battlefield situations and pre-war propaganda, as evidenced in recent local wars. The cost of war would thus decrease significantly, leading to new forms of warfare. Would small and weak nations still have a chance? Can the will to fight be changed without bloodshed? Is “force” no longer a necessary condition for the definition of war?

  The form of war may change, but its essence remains. Regardless of how “bloody” war is, it will still force the enemy to submit to its will and inflict significant “collateral damage,” only the methods of confrontation may be entirely different. The essence of war lies in the deep-seated “human nature,” which is determined by culture, history, behavior, and values. It is difficult to completely replicate using any artificial intelligence technology. Therefore, we cannot outsource all ethical, political, and decision-making issues to artificial intelligence, nor can we expect it to automatically generate “human nature.” Artificial intelligence technology may be abused due to impulsive passions, so it must be under human control. Since artificial intelligence is trained by humans, it will never be without bias, so it cannot be completely free from human supervision. In the future, artificial intelligence can become a creative tool or partner, enhancing “tactical imagination,” but it must be “aligned” with human values. These issues require continuous reflection and understanding in practice.

  Will AGI revolutionize war theory?

  Most academic knowledge is expressed in natural language. A comprehensive language model, encompassing the vast body of human writing, can connect seemingly incompatible linguistic works with scientific research. For example, some have input classical works, and even works from philosophy, history, political science, and economics, into a comprehensive language model for analysis and reconstruction. They’ve found that it can comprehensively analyze all scholars’ viewpoints and also offer its own “insights,” without sacrificing originality. Therefore, some have suggested that AGI could also be used to re-analyze and interpret war theory, stimulating human innovation and driving significant evolution and reconstruction of war theory and its systems. Perhaps theoretically, this could indeed lead to some improvements and developments, but war science is not only theoretical but also practical, and practicality and realism are fundamentally beyond AGI’s capabilities. Can classical war theory truly be reinterpreted? If so, what is the significance of the theory?

  In short, AGI’s disruptive impact on the concept of warfare will far exceed “mechanization” and “informatization.” We must embrace AGI boldly, yet remain cautious. Understanding the concept prevents ignorance; in-depth research prevents falling behind; and strengthened oversight prevents oversight. How to cooperate with AGI and guard against adversaries’ AGI technological surprise attacks is our primary concern for the future. (Rong Ming, Hu Xiaofeng)

 Postscript

  Think ahead and envision the future with an open mind

  Futurist Roy Amara famously asserted that people tend to overestimate the short-term benefits of a technology while underestimating its long-term impact, a principle known as “Amara’s Law.” This law emphasizes the non-linear nature of technological development, meaning that the actual impact of technology often only becomes fully apparent over a longer timescale. It reflects the pulse and trends of technological development, and embodies humanity’s acceptance and aspirations towards technology.

  Currently, in the development of artificial intelligence from weak AI to strong AI, and from specialized AI to general AI, every time people think they have completed 90% of the process, looking back, they may have only completed less than 10%. The driving role of technological revolution in military revolution is becoming increasingly prominent, especially as high-tech, represented by AI, penetrates the military field in multiple ways, profoundly changing the mechanisms, elements, and methods of winning wars.

  In the foreseeable future, intelligent technologies such as AGI will continue to iterate, and the cross-evolution of intelligent technologies and their empowering applications in the military field will become increasingly diversified, perhaps even transcending the boundaries of humanity’s current understanding of warfare. The development of technology is unstoppable, and no one can halt it. Whoever can use keen insight and a clear mind to see the trends and future of technology, to recognize its potential and power, and to penetrate the “fog of war,” is more likely to seize the initiative and gain the upper hand.

  This reminds us that exploring the future forms of warfare requires a broader perspective and more nuanced thinking to get closer to the underestimated reality. Where is AGI headed? Where is intelligent warfare headed? These questions test human wisdom. (Ye Chaoyang)

現代國語:

通用人工智慧及其對戰爭的影響

編按

科技與戰爭密不可分。科技創新不斷改變戰爭的面貌,卻並未改變戰爭的暴力本質與脅迫目的。近年來,隨著人工智慧(AI)技術的快速發展和應用,關於其對戰爭影響的爭論從未停止。與人工智慧(AI)相比,通用人工智慧(AGI)擁有更高層次的智能,被認為是一種可與人類智能相媲美的智能形式。 AGI的出現將如何影響戰爭?它會改變戰爭的暴力和脅迫本質嗎?本文將透過一系列思考來探討這個問題。

AGI只是一種賦能技術嗎?

許多人認為,儘管大規模模型和生成式人工智慧展現了AGI強大的軍事應用潛力,但它們最終只是賦能技術。它們只能增強和優化武器裝備,使現有裝備更加智能,提高作戰效率,但不太可能帶來真正的軍事革命。正如「網路戰武器」最初出現時曾被許多國家寄予厚望,但現在看來,這些期望有些過高。

通用人工智慧(AGI)的顛覆性本質則截然不同。它以遠超人類的反應速度和知識水平,為戰場帶來深刻變化。更重要的是,它促進了技術的快速發展,從而產生巨大的顛覆性影響。在未來的戰場上,AGI將賦予自主武器先進的智能,使其性能全面提升,並憑藉其速度和集群優勢,成為「攻守難攻」的武器。屆時,一些科學家預測的高智慧自主武器將成為現實,而AGI將在其中扮演至關重要的角色。目前,人工智慧的軍事應用包括自主武器、情報分析、智慧決策、智慧訓練和智慧支援等,這些應用很難簡單地用「賦能」來概括。此外,通用人工智慧(AGI)發展迅速,迭代周期短,並且不斷演進。未來的戰爭需要優先考慮AGI,並密切關注其潛在的變化。

AGI會讓戰爭消失嗎?

歷史學家杰弗裡·布萊尼認為,“戰爭總是由於對彼此實力或意志的誤判而發生的”,而隨著AGI在軍事領域的應用,誤判將變得越來越少見。因此,一些學者推測戰爭將會減少甚至消失。的確,依賴AGI可以顯著減少誤判,但即便如此,也無法完全消除不確定性,因為不確定性是戰爭的本質特徵。此外,並非所有戰爭都源自於誤判,AGI固有的不可預測性和不可解釋性,以及缺乏使用AGI的經驗,將會帶來新的不確定性,使人們陷入更深的「人工智慧迷霧」。

通用人工智慧(AGI)演算法也帶來了理性方面的挑戰。一些學者認為,AGI挖掘和準確預測關鍵情報的能力具有雙重影響力。在實踐中,AGI確實比人類犯錯更少,提高了情報準確性並減少了誤判;然而,它有時會導致過度自信,並助長魯莽行動。 AGI帶來的進攻優勢使得最佳防禦策略成為“先發製人”,打破了攻防平衡,引發了新的安全困境,並最終增加了戰爭風險。

AGI(自動生成技術)用途廣泛,易於整合到武器系統中。與核武、生物武器和化學武器不同,AGI的進入門檻低,且極易擴散。由於各國之間存在技術差距,不成熟的AGI武器有可能部署到戰場上,造成重大風險。例如,無人機在近期局部戰爭中的應用促使許多中小國家開始大規模採購無人機。通用人工智慧(AGI)提供的低成本裝備和技術很可能引發一場新的軍備競賽。

通用人工智慧會成為終極威懾力量嗎?

威懾是指維持一種能力,使對手不敢採取超越自身利益的行動。終極威懾是指威懾力強大到無法使用,例如確保相互毀滅的核威懾。但最終,決定戰爭結果的是「人性」——這是戰爭中永遠不可或缺的關鍵因素。

如果忽略「人性」因素,通用人工智慧會成為強大的威懾力量嗎?通用人工智慧速度很快,但缺乏同理心。其執行果斷,嚴重壓縮了戰略迴旋空間。通用人工智慧(AGI)是未來戰場上的關鍵因素,但由於缺乏實戰經驗,準確評估其能力十分困難,容易導致高估對手實力。此外,關於自主武器控制,究竟是安排人員在現場進行全面監督,還是安排人員遠端操控,完全放權,無疑需要慎重考慮。智慧武器的發射控制權能否移交給AGI?如果不能,威懾效果將大大降低;如果可以,人類的生死真的能由與他們無關的機器來決定嗎?康乃爾大學的研究表明,即使在中立國,大規模兵棋推演模型也經常會透過「突然的核攻擊」來升級戰爭。

或許在未來的某一天,AGI的能力將超越人類,使我們無法對其進行監管和控制。 「深度學習」一詞的創造者傑弗裡·辛頓表示,他從未見過智能水平更高的系統被智能水平較低的系統控制的情況。一些研究團隊認為,人類或許無法監管超級人工智慧。未來,面對強大的通用人工智慧(AGI),我們真的能夠控制它們嗎?這是一個值得深思的問題。

通用人工智慧會改變戰爭的本質嗎?

隨著通用人工智慧的廣泛應用,充滿暴力和血腥的戰場會消失嗎?有人認為,人工智慧戰爭的能力遠遠超過人類,甚至可能將人類擠出戰場。當人工智慧將戰爭完全轉變為自主機器人之間的衝突時,它還會是「暴力和血腥的戰爭」嗎?當能力懸殊的對手對抗時,較弱的一方可能根本沒有機會採取行動。戰爭能否透過兵棋推演在爆發前就結束?通用人工智慧會從根本改變戰爭的本質嗎?一場無人幹預的「戰爭」還能稱之為戰爭嗎?

《人類簡史》的作者尤瓦爾·赫拉利指出,所有人類行為都受語言影響,並影響我們的歷史。通用人工智慧(AGI)是AGI的典型例子,它與其他發明不同之處在於能夠創造全新的想法和文化。 「能夠講述故事的人工智慧將改變人類歷史的進程。」當AGI掌控語言時,人類建立的整個文明體係都可能被顛覆,甚至無需AGI發展出意識。就像柏拉圖的洞穴寓言一樣,人類會把AGI當成新的「神」嗎?

AGI(人工智慧生成設備)透過人類語言與人類建立密切聯繫,並改變人類的感知,使其難以辨認和識別。這帶來了一個風險:人類的戰鬥意志可能被別有用心之人所操控。哈拉里指出,電腦無需部署殺手機器人;如有必要,它們將允許人類自行扣動扳機。通用人工智慧(AGI)能夠精確地製造和完善態勢訊息,並透過深度偽造技術控制戰場感知。正如近期局部戰爭所證明的那樣,無人機可以透過偽造戰場態勢和戰前宣傳來實現這一點。戰爭成本將因此大幅降低,進而催生新的戰爭形式。弱小國還有勝算?能否在不流血的情況下改變人們的戰鬥意志? 「武力」是否不再是戰爭定義的必要條件?

戰爭的形式或許會改變,但本質不變。無論戰爭多麼“血腥”,它仍然會迫使敵人屈服於其意志,並造成重大的“附帶損害”,只是對抗的方式可能截然不同。戰爭的本質在於根深蒂固的“人性”,而人性又由文化、歷史、行為和價值觀所決定。任何人工智慧技術都難以完全複製人性。因此,我們不能將所有倫理、政治和決策問題都外包給人工智慧,也不能指望它會自動產生「人性」。人工智慧技術可能因衝動而濫用,因此必須受到人類的控制。由於人工智慧是由人類訓練的,它永遠無法完全消除偏見,因此也無法完全脫離人類監督。未來,人工智慧可以成為一種創造性的工具或夥伴,增強“戰術想像”,但它必須與人類價值觀“保持一致”。這些問題需要在實踐中不斷反思和理解。

通用人工智慧(AGI)會徹底改變戰爭理論嗎?

大多數的學術知識都是用自然語言表達。一個涵蓋人類浩瀚文字的綜合語言模型,可以將看似不相容的語言作品與科學研究連結起來。例如,一些研究以古典著作為輸入,甚至以…為輸入。從哲學、歷史、政治學和經濟學等領域汲取靈感,建構出一個用於分析和重構的綜合語言模型。研究發現,該模型能夠全面分析所有學者的觀點,並提出自身的“洞見”,同時又不失原創性。因此,有人提出,通用人工智慧(AGI)也可用於重新分析和詮釋戰爭理論,從而激發人類創新,推動戰爭理論及其體系的重大演進和重構。理論上,這或許確實能夠帶來一些改進和發展,但戰爭科學不僅是理論性的,也是實踐性的,而實踐性和現實性從根本上來說超出了AGI的能力範圍。經典戰爭理論真的可以被重新詮釋嗎?如果可以,那麼該理論的意義何在?

簡而言之,AGI對戰爭概念的顛覆性影響將遠遠超越「機械化」和「資訊化」。我們必須大膽擁抱AGI,但也要保持謹慎。理解概念可以避免無知;深入研究可以避免落後;加強監督可以避免監督的缺失。如何與通用人工智慧(AGI)合作,並防範對手利用AGI發動的技術突襲,是我們未來面臨的首要問題。 (榮明,胡曉峰)

後記

以開放的心態展望未來

未來學家羅伊·阿馬拉曾提出一個著名的論點:人們往往高估一項技術的短期收益,而低估其長期影響,這一原則被稱為「阿馬拉定律」。該定律強調了技術發展的非線性特徵,這意味著技術的實際影響往往需要更長的時間才能完全顯現。它反映了技術發展的脈動和趨勢,反映了人類對科技的接受度和期望。

目前,在人工智慧從弱人工智慧向強人工智慧、從專用人工智慧發展到通用人工智慧的過程中,每當人們認為自己已經完成了90%的工作時,回頭來看,他們可能只完成了不到10%。科技革命在軍事革命中的驅動作用日益凸顯,尤其是在人工智慧(AI)等高科技以多種方式滲透軍事領域,深刻改變戰爭的機制、要素和製勝方法的情況下。

在可預見的未來,通用人工智慧(AGI)等智慧技術將不斷迭代,智慧技術的交叉演進及其在軍事領域的賦能應用將日益多元化,甚至可能超越人類目前對戰爭的認知邊界。技術發展勢不可擋,無人能阻擋。誰能以敏銳的洞察力和清晰的思維洞察技術的趨勢和未來,認識到其潛力和力量,並撥開“戰爭迷霧”,誰就更有可能搶佔先機,取得優勢。

這提醒我們,探索未來戰爭形態需要更廣闊的視野和更細緻的思考,才能更接近被低估的現實。通用人工智慧將走向何方?智慧戰爭將走向何方?這些問題考驗的是人類的智慧。 (葉朝陽)

中國原創軍事資源:https://www.news.cn/milpro/20250121/18eb7781b268d26489286b08c2d23d12084f0f/c.html

A Look at Chinese Intelligent Warfare | Machine Thinking: The Key to Victory in Military Intelligent Warfare

中國情報戰概覽 | 機器思維:軍事情報戰取勝的關鍵

現代英語:

Editor’s Note

In the 1950s, scientist Alan Turing first proposed the concept of “machine thinking.” With the advent of the intelligent era, the idea that machines can also possess “thinking” is gradually becoming a reality. In intelligent warfare, driven by machine thinking, some unmanned equipment and decision-making aids become “robot allies” and “intelligent advisors” fighting alongside humans. It is foreseeable that the relationship between humans and weapons will gradually shift from that of humans and tools to that of humans and intelligent partners with “limited subjective initiative.” A deep understanding and skillful application of machine thinking as a key will help people recognize the characteristics of intelligent warfare and seize the initiative in it.

In recent years, next-generation artificial intelligence technologies, represented by deep learning, have made groundbreaking progress, surpassing humans in many fields such as Go, speech recognition, and translation. More and more people are beginning to realize that the human brain is merely a highly advanced general-purpose intelligent agent; human intelligence is not the only form of intelligence in the world, nor is it the ultimate form of intelligence. Human society is entering an era of intelligent coexistence between humans and machines. All preparations for intelligent warfare, including exploring the mechanisms for winning intelligent warfare, developing intelligent weapons and equipment, developing intelligent combat forces, and innovating intelligent combat methods, should be based on a thorough understanding of how intelligent machines “think.”

Machine thinking is developing rapidly

From mechanical technology to information technology and then to artificial intelligence, technological development has progressed from simulating human limb functions, sensory functions, neural functions, and finally cognitive functions, gradually replacing, expanding, and amplifying various human abilities, progressing from simple to complex and from low to high levels. As a replacement for the human brain, the most complex organ in the human body, artificial intelligence must possess “thinking” abilities similar to those of the human brain in solving complex problems; we can call this “machine thinking.”

The new generation of artificial intelligence systems based on deep learning can be viewed as a “gray box” compared to the previous generation, with its “thinking” process and results exhibiting significant uncertainty and inexplicability. While people hope it can be explained, from another perspective, it is precisely this uncertainty and inexplicability that generates creativity and constitutes the true “source of wisdom.” Higher forms of human thought, besides logical reasoning, such as intuition, imagination, inspiration, and sudden insight, all possess a high degree of uncertainty and can only be understood intuitively, not explained in words. Just as the art of command in the military, where “the subtlety of application lies in the mind,” is difficult to explain.

Therefore, the uncertainty and inexplicability exhibited by machine thinking may precisely be the advanced and unique aspect of this breakthrough in artificial intelligence. No matter how fast a supercomputer or quantum computer is, or how powerful its computational intelligence is, because its computational principles are transparent and interpretable, its computational rules are pre-designed and deterministic, and its computational process is reversible and repeatable, people do not consider it creative or a challenge to human thinking abilities.

This breakthrough in artificial intelligence has significantly improved the “intelligence” of intelligent machines, with machine thinking demonstrating unique advantages in many fields that differ from and surpass human thinking. For example, after AlphaGo defeated the human world Go champion, some believed it was closer to the god of Go, creating a completely new school of Go like the “cosmic style,” and some Go players even began to learn from AlphaGo’s playing style. Furthermore, generative AI like ChatGPT, which has become incredibly popular in the last two years, already possesses a certain degree of creativity and human-like “subjective initiative,” enabling it to replace humans in many tasks.

Machine thinking is different from human thinking.

Currently, although artificial intelligence has made groundbreaking progress, it is still in the development stage of perceptual intelligence, weak AI, and specialized AI. Compared with human thinking, machine thinking still has obvious shortcomings. Experts have summarized its deficiencies into four points: First, it “has intelligence but lacks wisdom,” lacking intuition, inspiration, and other implicit human thinking abilities. Einstein once said that raising a question is often more important than solving a problem. ChatGPT is far better than the average person at answering questions, but it cannot raise a truly valuable scientific question. Second, it “has IQ but lacks EQ.” Intelligent machines themselves do not have, and find it difficult to, simulate human emotions such as anger, sadness, and joy, and therefore cannot truly understand these human emotions. Third, they are “good at calculation but not at scheming.” Although intelligent machines “think” very quickly, they are not good at taking roundabout ways or retreating to advance. They cannot pretend, deceive, or use tricks like humans. Fourth, they are “good at specialization but not generalization.” Intelligent machines have poor “learning by analogy,” that is, their ability to transfer learning is very poor. Although specialized artificial intelligence software can surpass human champions in Go, the “intelligence” of the most advanced general-purpose brain-like chips can only approach the level of a mouse brain.

Although machine thinking was created and designed by humans, it differs significantly from human thinking. There’s a Moraviek paradox in the field of artificial intelligence: for AI, achieving complex logical reasoning and other high-level human cognitive abilities requires minimal computation, while achieving unconscious skills like perception and movement, and simpler cognitive abilities like intuition, demands enormous computational power. AI can outperform humans in playing Go and solving equations, but tasks easy for humans, like driving a car or folding clothes, are very difficult for AI. Experts have outlined what AI currently cannot do, including: cross-domain reasoning, abstract thinking, self-awareness, aesthetics, and emotion. These are not difficult for humans, but are very challenging for AI.

Based on the differences between machine thinking and human thinking, in intelligent warfare, on the one hand, traditional strategies that work for humans, such as feints and diversions, are likely to be easily detected by machine thinking; the massive amounts of battlefield data, far exceeding the analytical processing capabilities of the human brain, will become the “thinking” material for machine thinking, allowing it to find clues about enemy actions and important targets. On the other hand, machine thinking also has some major flaws that seem utterly “idiotic” to humans. Foreign research teams have discovered that by changing just a few key pixels in a picture of a cat, an intelligent machine can identify the cat as a dog, while the human eye will not misidentify it due to this change. This illustrates a significant difference between deceiving humans and deceiving intelligent machines. The “calculations” used to deceive humans may be useless against the “calculations” of intelligent machines. Conversely, deception methods targeting machine thinking are very easy to use to fool intelligent machines, but may not be able to fool humans. With the deep application of artificial intelligence in intelligence analysis, further research is needed on how strategic deception is organized, how battlefield feints are implemented, how to deceive both human and computer brains, how to attack the weaknesses of adversary intelligent machines, and how to prevent one’s own intelligent machines from being deceived.

All of the above facts show that the complexity problems faced by humans and machines may be exactly opposite. Humans and machines each have their own advantages and disadvantages and are highly complementary. Through human-machine collaboration, humans can be responsible for judging whether they are “doing the right thing” while machines “do things correctly”.

Create machine thinking based on machine characteristics

The carrier of machine thinking is silicon-based chips, but it is not endogenous; rather, it is created by humans using innovative thinking. The level of human creators’ thinking determines the level of machine thinking. A key point to grasp in creating machine thinking is that it cannot be simply copied from human thinking methods based on carbon-based intelligence. Instead, it should be created according to the characteristics of silicon-based machines in terms of perception, judgment, decision-making, and action.

For example, how do cars pass through intersections? For manned vehicles, a complete set of mature rules has been established to avoid congestion and traffic accidents. But how can autonomous vehicles pass through without collisions? There are at least three solutions. First, the autonomous vehicle stops at the intersection and uses its onboard camera to mimic human eyes, automatically recognizing and judging traffic light changes, and only proceeding when the light turns green. Second, a signal generator is installed on the traffic light pole; when the green light is on, it directly emits a signal indicating passage, which the autonomous vehicle receives before proceeding. Third, traffic lights are eliminated; the autonomous vehicle uses sensors such as lidar, cameras, and millimeter-wave radar to detect passing vehicles at the intersection, employing collision avoidance algorithms and vehicle-to-vehicle cooperation to pass quickly and without interruption. The first approach is to design the driving method of autonomous vehicles according to human driving thinking and behavioral habits. The second approach is an improvement on the first approach. The third approach completely subverts the traditional mode of human vehicles relying on traffic lights and passing through intersections in a “stop-wait-go” manner, which greatly improves traffic efficiency and is equivalent to giving autonomous vehicles a machine thinking that truly suits their own characteristics.

Massively creating machine thinking to seize intelligent advantage

Machine thinking is essentially algorithmic thinking, digital thinking, and precision thinking. In intelligent warfare, in order to make one’s own intelligent machines “smarter” than the opponent’s and to seek to overwhelm the opponent’s intelligent advantage, we should create a large number of different types of high-level machine thinking and greatly improve the ability of intelligent machines to adapt to changing battlefield environments and solve complex combat problems.

For example, creating machine thinking that enables unmanned swarms to collectively understand the battlefield situation. A fundamental prerequisite for efficient collaborative operations between combat units is a shared understanding of the battlefield situation. For humans, the most intuitive and effective method is based on a unified battlefield situation map. However, this approach is unsuitable for collaborative operations between unmanned platforms within a swarm. This is because using visual diagrams as a medium for machine-to-machine communication is inefficient, and it is difficult for unmanned platforms to directly extract useful information from battlefield situation maps. Therefore, a dedicated battlefield situation sharing mechanism adapted to machine-to-machine communication is needed. For instance, leveraging the fact that intelligent machines are more efficient at “counting” than “viewing images,” the unmanned swarm can use software to create a virtual “bulletin board,” i.e., a shared data file. In collaborative operations, each drone platform promptly publishes its own location and status, as well as the nature, location, and environmental information of targets detected by its sensors, to the “bulletin board.” All drone platforms in the cluster can quickly read this shared data file to obtain near-real-time information on the enemy, ourselves, and the environment, thereby achieving a shared understanding of the battlefield situation.

Another example is the development of machine thinking for integrated offensive and defensive warfare using unmanned platforms. The basic principle of warfare, “eliminate the enemy, preserve yourself,” is easily understood by human soldiers, but enabling unmanned platforms to correctly balance avoiding enemy threats and engaging enemy targets requires a different approach. Utilizing artificial potential field algorithms might be one solution. Unmanned platforms could construct a repulsive potential field around targets that pose a threat, with stronger repulsion due to greater threat; and a gravitational potential field around targets intended for attack, with stronger attraction due to higher target value. Under the combined influence of these gravitational and repulsive potential fields, the unmanned system automatically generates the optimal attack path, thus maximizing the achievement of both eliminating the enemy and preserving itself.

現代國語:

編按

在1950年代,科學家艾倫·圖靈首次提出了「機器思維」的概念。隨著智慧時代的到來,機器也能擁有「思維」的概念逐漸成為現實。在由機器思維驅動的智慧戰爭中,一些無人裝備和決策輔助工具正成為與人類並肩作戰的「機器人盟友」和「智慧顧問」。可以預見,人與武器的關係將逐漸從人與工具的關係轉變為人與擁有「有限主觀主動性」的智慧夥伴的關係。深入理解並巧妙運用機器思維是關鍵,有助於人們認識智慧戰爭的特點,並在其中掌握主動權。

近年來,以深度學習為代表的新一代人工智慧技術取得了突破性進展,在圍棋、語音辨識、翻譯等諸多領域超越了人類。越來越多的人開始意識到,人腦只不過是一個高度發展的通用智能體;人類智能並非世間唯一的智能形式,也並非智能的終極形式。人類社會正步入人機智慧共存的時代。一切智慧戰爭的準備工作,包括探索智慧戰爭的致勝機制、研發智慧武器裝備、發展智慧作戰力量以及創新智慧作戰方法,都應建立在對智慧機器「思考」方式的透徹理解之上。

機器思維正在快速發展

從機械技術到資訊技術,再到人工智慧,技術發展經歷了從模擬人體肢體功能、感覺功能、神經功能,最終到認知功能的演進,逐步取代、擴展和增強了人類的各種能力,由簡到繁、由低到高不斷演進。作為人體最複雜器官——人腦的替代品,人工智慧必須具備與人腦類似的「思考」能力,能夠解決複雜問題;我們可以稱之為「機器思維」。

與上一代人工智慧系統相比,基於深度學習的新一代人工智慧系統可以被視為一個“灰箱”,其“思考”過程和結果都展現出顯著的不確定性和不可解釋性。人們雖然希望能夠解釋這些過程,但從另一個角度來看,正是這種不確定性和不可解釋性激發了創造力,構成了真正的「智慧之源」。除了邏輯推理之外,更高層次的人類思維,例如直覺、想像、靈感和頓悟,都具有高度的不確定性,只能透過直覺來理解,而無法用語言來解釋。正如軍事指揮的藝術一樣,“運用之妙在於心智”,難以言表。

因此,機器思維所展現出的不確定性和不可解釋性,或許正是人工智慧這項突破的先進之處與獨特之處。無論超級電腦或量子電腦的速度有多快,計算智慧有多強大,由於其計算原理透明且可解釋,計算規則預先設計且具有確定性,計算過程可逆且可重複,人們並不認為它具有創造性,也不認為它對人類思維能力構成挑戰。

人工智慧的這一突破顯著提升了智慧機器的“智慧”,機器思維在許多領域展現出與人類思維截然不同甚至超越人類思維的獨特優勢。例如,AlphaGo擊敗人類圍棋世界冠軍後,有些人認為它更接近圍棋之神,開創了「宇宙流」等全新圍棋流派,甚至有圍棋選手開始學習AlphaGo的棋風。此外,像ChatGPT這樣在過去兩年迅速走紅的生成式人工智慧,已經具備一定程度的創造力和類似人類的“主觀主動性”,使其能夠在許多任務中取代人類。

機器思維與人類思維截然不同。

目前,人工智慧雖然取得了突破性進展,但仍處於感知智慧、弱人工智慧和專業人工智慧的發展階段。與人類思維相比,機器思維仍有明顯的缺點。專家將其缺陷歸納為四點:首先,它“有智能但缺乏智慧”,缺乏直覺、靈感等人類固有的思維能力。愛因斯坦曾說過,提出問題往往比解決問題重要。 ChatGPT在回答問題上遠勝於一般人,但它無法提出真正有價值的科學問題。其次,它「有智商,但缺乏情商」。智慧機器本身並不具備,也很難模擬人類的情感,例如憤怒、悲傷和喜悅,因此無法真正理解這些人類情感。第三,它們「擅長計算,但不擅長規劃」。雖然智慧機器「思考」速度很快,但它們不擅長迂迴策略或退守後再前進。它們無法像人類那樣偽裝、欺騙或使用詭計。第四,它們「擅長專業化,但不擅長泛化」。智慧機器的「類比學習」能力很差,也就是說,它們的學習遷移能力非常弱。雖然專業的AI軟體可以在圍棋領域超越人類冠軍,但最先進的通用類腦晶片的「智慧」水平也只能接近小鼠大腦的水平。

儘管機器思維是由人類創造和設計的,但它與人類思維有顯著差異。人工智慧領域存在著一個莫拉維克悖論:對於人工智慧而言,實現複雜的邏輯推理和其他高級人類認知能力所需的計算量極少,而實現諸如感知和運動等無意識技能以及諸如直覺等更簡單的認知能力卻需要巨大的計算能力。人工智慧在圍棋和解方程式方面可以超越人類,但對人類來說輕而易舉的任務,例如開車或疊衣服,對人工智慧來說卻非常困難。專家們已經列出了人工智慧目前無法完成的任務,包括:跨領域推理、抽象思考、自我意識、美學和情感。這些對人類來說並不難,但對人工智慧來說卻極具挑戰性。

基於機器思維和人類思維的差異,在智慧戰爭中,一方面,對人類有效的傳統策略,例如佯攻和佯攻,很可能被機器思維輕易識破;另一方面,海量的戰場數據遠遠超過人腦的分析處理能力,將成為機器思維的「思考」素材,使其能夠從中發現敵方行動和重要目標的線索。另一方面,機器思維也存在著一些在人類看來極為「愚蠢」的重大缺陷。國外研究團隊發現,只要改變貓咪的圖片中幾個關鍵像素,智慧機器就能將貓辨識為狗,人眼卻不會因此而誤判。這說明欺騙人類和欺騙智慧機器之間存在顯著差異。用來欺騙人類的「計算」可能對智慧機器的「計算」毫無作用。反之,針對機器思維的欺騙方法很容易就能欺騙智慧機器,但卻可能無法欺騙人類。隨著人工智慧在情報分析領域的深度應用,我們需要進一步研究戰略欺騙的組織方式、戰場佯攻的實施方法、如何同時欺騙人類和電腦的大腦、如何攻擊敵方智慧機器的弱點以及如何防止己方智慧機器被欺騙。

以上種種事實表明,人類和機器面臨的複雜性問題可能截然相反。人類和機器各有優劣,高度互補。透過人機協作,人類負責判斷自己“是否在做正確的事”,而機器則負責“正確地做事”。

基於機器特性創造機器思維

機器思維的載體是矽晶片,但它並非內生的,而是由人類運用創新思維創造出來的。人類創造者的思維層次決定了機器思維的層次。創造機器思維的關鍵在於,它不能簡單地複製基於碳基智能的人類思維方式,而應該根據矽基機器在感知、判斷、決策和行動等方面的特性來創造。

例如,汽車如何通過十字路口?對於有人駕駛的車輛,已經建立了一套完整的成熟規則來避免擁擠和交通事故。但是,自動駕駛車輛如何才能無碰撞地通過十字路口呢?至少有三種解決方案。首先,自動駕駛車輛在十字路口停車,利用車載攝影機模擬人眼,自動辨識並判斷交通號誌的變化,僅在綠燈亮起時才通行。其次,在交通號誌桿上安裝號誌產生器;當綠燈亮起時,它直接發出通行訊號,自動駕駛車輛接收到該號誌後再通行。第三,取消交通號誌;自動駕駛車輛使用光達、攝影機和毫米波接收器等感測器進行通訊。ADA 系統用於偵測十字路口的過往車輛,利用防碰撞演算法和車對車協作實現快速無間斷通行。第一種方法是根據人類駕駛的思考和行為習慣來設計自動駕駛車輛的駕駛方式。第二種方法是對第一種方法的改進。第三種方法徹底顛覆了人類車輛依賴交通號誌、以「停-停-走」方式通過十字路口的傳統模式,大大提高了交通效率,相當於賦予自動駕駛車輛真正符合自身特性的機器思維。

大規模建構機器思維,奪取智慧優勢

機器思維本質上是演算法思維、數位思維和精確思維。在智慧戰爭中,為了使己方智慧機器比敵方更“聰明”,並力求壓倒敵方的智慧優勢,我們應該構建大量不同類型的高級機器思維,並大幅提升智慧機器適應不斷變化的戰場環境和解決複雜作戰問題的能力。

例如,創造一種機器思維,使無人集群能夠集體理解戰場態勢。作戰單位間高效率協同作戰的基本前提是對戰場態勢的共同理解。對人類而言,最直觀有效的方法是基於統一的戰場態勢圖。然而,這種方法並不適用於集群內無人平台之間的協同作戰。這是因為使用視覺化圖表作為機器間通訊的媒介效率低下,無人平台難以直接從戰場態勢圖中提取有用資訊。因此,需要一種專門針對機器間通訊的戰場態勢共享機制。例如,利用智慧機器更擅長“計數”而非“查看圖像”的特性,無人集群可以使用軟體創建一個虛擬的“公告板”,即共享資料檔案。在協同作戰中,每個無人機平台都會及時將自身位置和狀態,以及其感測器探測到的目標的性質、位置和環境資訊發佈到「公告板」上。集群中的所有無人機平台都能快速讀取共享數據文件,獲取近乎實時的敵我信息以及周圍環境信息,從而實現對戰場態勢的共同理解。

另一個例子是利用無人平台發展機器思維,以進行攻防一體化作戰。戰爭的基本原則「消滅敵人,保全自身」對人類士兵來說很容易理解,但要使無人平台能夠正確地平衡規避敵方威脅和攻擊敵方目標,則需要不同的方法。利用人工勢場演算法或許是一種解決方案。無人平台可以在構成威脅的目標周圍建構排斥位勢場,威脅越大,排斥力越強;在攻擊目標周圍建構重力位勢場,目標價值越高,引力越強。在這些重力位能場和排斥位勢場的共同作用下,無人系統能夠自動生成最佳攻擊路徑,從而最大限度地實現消滅敵人和保全自身的目標。

來源:中國軍網-解放軍報 作者:袁 藝 責任編輯:尚曉敏 發布:2024-02-27 06:xx:xx

袁  藝

中國原創軍事資源:http://www.81.cn/ll_208543/1868289808681.html

Chinese Military Reflections on the Application of AI in Human-Machine Integrated Combat

中國軍方對人工智慧在人機一體化作戰中應用的思考

現代英語:

The principle of training troops to fight future battles is a fundamental tenet of military strategy throughout history. An army that does not study and predict warfare is a foolish army, destined to fail when war strikes.

To date, there have been four major military transformations in the world: the first was the shift from primarily using wooden and stone weapons to primarily using metal weapons; the second was the shift from primarily using cold weapons (metal weapons) to primarily using firearms (gunpowder weapons); the third was the shift from firearms to mechanized weapons; and the fourth occurred after the 1990 Gulf War, when warfare shifted from primarily using mechanized weapons to primarily using precision-guided weapons, driving the transformation of military development from mechanization to informatization.

The fourth military revolution, also known as the new military revolution by academics, involves the world’s major military powers engaging in comprehensive competition in areas such as information technology, network technology, precision-guided technology, aerospace technology, new energy technology, biotechnology, and stealth technology. This competition has now culminated in the pursuit of advantages in big data, cloud computing, and intelligent robots, aiming to create real-life versions of “Iron Man,” “Batman,” and “Terminator.” The revolution is actively promoting the transformation of military construction from informatization and networking to intelligentization and unmanned aerial vehicle (UAV) deployment. The military is developing towards a lean, small, efficient, intelligent, and integrated “human-machine (robot/UAV)” model, seeking to enable robot soldiers, UAVs, and human soldiers to fight together.

According to statistics, the militaries of more than 60 countries worldwide have already equipped themselves with military robots, encompassing over 150 different types. It is projected that by 2040, half of the world’s major military powers may be comprised of robots. In addition to the US, Russia, the UK, France, Japan, Israel, Turkey, and Iran, which have already launched their own robot warriors and drones, other countries are also investing in the research and development of unmanned weapons, which will inevitably give rise to unmanned combat forces.

The term “unmanned combat force” is a general term for combat robots or battlefield killing robot systems. With the development of various information-based, precision-based, and data-driven weapons and equipment, intelligent platforms have become the driving force for pre-designed battlefields, combat robots have become the main force on the battlefield, and the combination of “human and machine” confrontation has become the key to defeating the enemy. In the future, the battlefield space forces will highlight the development trend of three-dimensional unmanned operation and human-machine integration across land, sea, and air.

In combat command and control, AI can automatically and rapidly generate combat plans. War is fought, but it is also designed. With the emergence of various information-based, precision, and intelligent weapons and equipment, and the widespread application of artificial intelligence, big data, and 5G networks, the future battlefield will essentially achieve integrated “human-machine” collaborative combat, inevitably revolutionizing traditional combat methods. Intelligent platforms, leveraging the advantages of big data, will become the behind-the-scenes directors of pre-designed battlefields, providing more accurate predictions and technical parameters, making future battlefield design more precise and efficient. Using AI technology, by inputting elements such as the deployment of enemy and friendly forces, equipment performance, personnel numbers, and battlefield environment into the combat command information system template, AI-based combat plans can be quickly generated for commanders’ operational decision-making. If commanders feel something is amiss and want to fight a battle they are confident of winning, they can also use intelligent simulated combat laboratories, employing artificial intelligence, big data, 5G networks, and simulation equipment and materials, to simulate the technical performance of enemy and friendly weapons and equipment, battlefield conditions, personnel quality, and combat actions, to test and refine the scientific and rational nature of the war design scheme, striving to find the optimal combat plan. 5G’s massive machine-to-machine communication capabilities can be combined with artificial intelligence to accelerate the comprehensive analysis and systematic research of combat effectiveness elements and combat processes using new intelligent algorithms, and to quickly derive combat capability assessment indices. This provides technical means for the large-scale use of unmanned weapons.

AI-generated combat plans differ from traditional automated combat command systems, though they share some similarities, they also have fundamental differences. In a sense, both are automated systems, but combat command automation, by inputting various combat elements, aims to output combat command decisions—these are essentially fixed. AI-generated combat plans, however, are different. The input combat elements can be fixed or variable, but the output is invariably unpredictable, almost entirely unpredictable. For example, even with the same total number of elements and parameters, different input orders will generate different results, potentially producing unexpected outcomes—this is the essence of artificial intelligence.

In terms of surprise in warfare, the coordinated operations of drones or manned aircraft have ushered in a new era. Night warfare, whether in the past or modern, has been a more effective way to achieve tactical and operational surprise. Today, night warfare is even more favored by informationized and intelligent armies. At night and in the early morning, people are in a state of sleep or semi-awakeness, and are relatively tired or complacent. Therefore, launching a war at this time makes it easier to achieve surprise. In the Kosovo War, the US launched its airstrikes at 8 PM. In the Afghan War, the US launched its airstrikes late at night. In the Iraq War, after launching its airstrikes at 5:36 AM, the US extensively used various means, including space reconnaissance satellites, aerial reconnaissance aircraft, and ground reconnaissance, to build a comprehensive information reconnaissance network system covering the air, space, and ground, firmly controlling “information superiority” and ensuring the smooth conduct of air strikes and nighttime ground military operations. With the development of night vision equipment and the increasing sophistication of night warfare methods, night and early morning have become common means of achieving surprise in air strikes. Seizing the favorable opportunities of darkness and early morning to launch surprise air strikes is the spark that will ignite future wars. Before the outbreak of future wars, unmanned reconnaissance aircraft will cooperate with manned high-altitude reconnaissance aircraft and space satellites to conduct reconnaissance of enemy forward and deep-space targets. In particular, once a drone detects a target, it can quickly transmit image information such as the target’s location and size to its own command center, drone operator, or manned aircraft pilot for decision-making reference and to issue long-range strike orders. During the Gulf War, multinational forces deployed drones to conduct day and night reconnaissance over Iraqi front-line positions, providing real-time images and guiding ground troops to destroy Iraqi positions. During the conflict between Armenia and Azerbaijan last year, Armenian media released a video showing the Armenian army using the Seahawk-10 drone to guide ground artillery attacks on Azerbaijani infantry units. In the video, the Armenian army’s Seahawk-10 drone transmitted information about a group of soldiers advancing in skirmish lines detected at high altitude to the drone operator. After several zoom-in confirmations, the drone operator used the drone to collect data on the target and transmit it to the artillery at the rear. After receiving the target coordinates, the Armenian artillery first conducted multiple single-shot test firings. The Seahawk-10 UAV then conducted real-time assessments of the test firing results in the air and promptly adjusted the target coordinate parameters to transmit to the Armenian artillery for concentrated and precise firing.

In future wars, drones are poised to replace conventional fighter jets, becoming one of the mainstays of aerial warfare. Their ability to execute precise, real-time strikes will revolutionize the traditional manned aircraft-based surprise attack methods employed in the dark or early morning. Currently, the UK is developing a new high-tech unmanned stealth fighter with stealth capabilities. It can test and drop munitions over multiple targets and defend itself against attacks from other manned and unmanned aircraft. Even without ground command, it can communicate with command centers via satellite and operate autonomously, executing precision strikes against long-range targets. Thus, drones, as a rapidly emerging force, have evolved from “reconnaissance and support” to “offensive protagonists.” They not only effectively supplement satellite reconnaissance but also perform diverse combat missions such as long-range reconnaissance, border patrol, target identification, electromagnetic interference, supply delivery, precision strikes, autonomous strikes, integrated reconnaissance and strike operations, and damage assessment. They are destined to become the vanguard in future wars.

On the land battlefield, unmanned tanks, unmanned armored vehicles, and combat robots are charging to the front lines, forming mixed formations with ground soldiers to fight collaboratively. To execute battlefield missions more efficiently and reduce casualties, future battlefields may see a large number of unmanned vehicles such as tanks, armored vehicles, and logistics transport vehicles. Leveraging the high speed, low latency, and interconnectivity of 5G networks, these vehicles can autonomously traverse various complex terrains and obstacles without human intervention, making instantaneous decisions to effectively ensure safety and reliability. Land robots can not only perform offensive and defensive combat missions but also deliver ammunition, medical supplies, and food, conduct patrols, and carry out reconnaissance and surveillance. Unmanned tanks allow soldiers to remotely control them, automatically load ammunition, and autonomously conduct indirect precision strikes. In 2019, Russia tested a robotic system called “Wooden Boat” to unify the command of several military robots. The Russian military and robotics research institutions also conducted collaborative exercises with newly developed combat robots, achieving good results and summarizing training methods in practice. According to Russian media reports, Russia is preparing to establish a combat robot force, a completely new type of military unit. These robots can achieve maximum automation, requiring minimal human intervention and essentially completing battlefield combat missions independently. Russian military-industrial complexes will begin developing the “Comrade” and “Assault” robot systems, composed of medium and heavy robots respectively, starting in 2020. They are currently working to improve the performance of some robots to better enable them to perform tasks in urban and coastal environments. In August 2015, on the Syrian battlefield, in addition to deploying traditional combat forces, the Russian military deployed for the first time a fully-fledged robot combat company, primarily composed of unmanned combat platforms, to conduct positional assault operations. Employing a new combat model of mixed manned and unmanned formations, they captured a high ground that Russian soldiers would find difficult to conquer in just 20 minutes, achieving a victory with zero casualties and 77 enemy kills. On April 21, 2018, the Russian Federal Security Service (FSB) special forces launched a raid against extremist terrorist groups, publicly deploying armed unmanned combat vehicles equipped with machine guns as the vanguard for the first time. Following large-scale testing of combat robots at an event called “Autonomous Warrior 2018,” the British Army has unified drones, unmanned vehicles, and combat personnel as a common practice for world-class militaries in the coming decades. The US Army, having formally established unmanned platoons, plans to form unmanned combat brigades and has already developed a standardized set of hardware and software. Once installed on vehicles, these can be remotely controlled, even semi-autonomously, automatically following predetermined routes or choosing the smoothest, most direct path, or driven by a human driver. One emerging project, the “optional manned tank,” aims to propel the Army into a new generation of joint operations. It may be capable of firing lasers, controlling drones, high-speed maneuvering, destroying enemy helicopters, penetrating enemy armored formations, and performing highly lethal robotic combat missions against enemy fire. The US Army has also made rapid progress in manned-unmanned combined arms operations. This means that robotic systems will increasingly operate with greater autonomy, while still being commanded and controlled by human decision-makers. Robotic vehicles deployed at the front lines can directly attack enemy mechanized formations at close range, launch weapons, perform high-risk surveillance missions, and deliver munitions when necessary. The U.S. Marine Corps tested its unmanned combat vehicle, nicknamed “Hunter Wolf,” in Arizona. Equipped with a 30mm M230LF “short-barreled” chain gun, the vehicle conducted a rapid-fire live-fire demonstration, achieving a perfect 6-for-6 hit. The “Hunter Wolf” is 2.3 meters long, 1.4 meters wide, and 1.17 meters high, weighing only 1.1 tons, yet capable of carrying a 450-kilogram modular combat payload. It uses a hybrid electric system, offering a maximum range of 100 kilometers without refueling, a top speed of 32 kilometers per hour, a maximum endurance of 72 hours, and the ability to climb slopes with a gradient of 30 degrees.

In the naval battlefield, unmanned ghost fleets, composed of unmanned surface and underwater vessels, are mixed with manned fleets and operate in coordinated formations. Since the 1990s, the increasing application of artificial intelligence and big data in the military field has ushered in a true golden age for unmanned surface and underwater vessels, giving rise to underwater robots (AUVs) and surface robots (ASVs). Various unmanned submarines and unmanned underwater vehicles perform a variety of tasks such as underwater search, reconnaissance, and mine clearance. Unmanned warships can travel thousands of miles and perform various maritime combat missions without onboard personnel. After the Iraq War in 2003, countries around the world saw the great potential and broad prospects of unmanned marine systems, which also reduce manpower and improve combat effectiveness, thus initiating a competition to build unmanned ghost fleets. Israel, as a country that places particular emphasis on reducing soldier casualties, took the lead in launching the development of modern “Protector” unmanned surface vessels, which are used to patrol the Lebanese coast and monitor Hezbollah activities and deployments. France and Russia already possess manned submersible research vessels capable of diving to depths of 6,000 meters. Japan has proposed a concept for the “Shinkai 12000,” a new manned submersible research vessel capable of diving to the world’s deepest point. Following its “Future Maritime Aviation Acceleration Day” event, the UK continues to develop a “plug-and-play” autonomous maritime platform development system. This system, once integrated into Royal Navy vessels, will simplify the acquisition and use of automation and unmanned technologies.

In the aerial battlefield, drones and manned aircraft are mixed in formation and cooperate in combat. In 2019, approximately 30 countries worldwide had developed over 50 types of drones, and more than 50 countries had deployed drones. The main types include: cryptographic drones, multi-functional drones, AI-powered drones, long-endurance drones, anti-missile drones, early warning drones, stealth drones, micro drones, air combat drones, mapping drones, aerial photography drones, armed drones, and drone wingmen. With the widespread application of advanced technologies such as artificial intelligence and big data in the military field, the performance of equipment on drones is constantly improving. They will integrate multiple functions such as reconnaissance, fire correction, surveillance, battle result assessment, target identification, attack guidance, radio relay, and ground attack. They can conduct electronic jamming and deception at long distances from the enemy, and can also autonomously attack important ground targets when necessary. The future aerial battlefield will essentially realize unmanned or human-machine (drone) cooperative air strikes, or autonomous drone air strikes, which will inevitably revolutionize traditional air combat methods. In the future, fighter pilots will control unmanned attack aircraft or bombers from their cockpits to evade enemy air defense systems, while offensive forces will receive real-time intelligence data more quickly—all thanks to the rapid advancements in artificial intelligence technology. In future air strikes, swarms of drones will swarm in, using sophisticated instruments for detection, reconnaissance, and counter-reconnaissance. Once they lock onto targets, they will calmly launch missiles, possessing integrated reconnaissance and strike capabilities, autonomous attack, and human-machine collaborative strike capabilities. The Russian Aerospace Forces will equip themselves with heavy attack drones capable of maneuvering around enemy air defense systems without command, autonomously searching for and striking the most important targets, and then retreating safely back to base. This aircraft will be equipped with artificial intelligence components and can be remotely controlled by Su-57 fighter jets. According to RIA Novosti, the Russian S-70 “Hunter” heavy attack drone can attack targets according to instructions issued from Su-57 stealth fighter jets. Currently, the control station where the “Hunter” ground operators are located is equipped with joysticks, keyboards, and several multi-function LCD screens, similar to those used in manned fighter jets. These screens display various information transmitted from the “Hunter’s” onboard systems and sensors. In the near future, this ground-based remote control equipment may achieve full automation. The S-70 “Hunter” UAV, developed by the Sukhoi Design Bureau, is designed and manufactured based on a flying wing aerodynamic layout. According to public information, the “Hunter” is 14 meters long, has a wingspan of 19 meters, and a takeoff weight of 20 tons. The “Hunter” has a maximum speed of 1000 kilometers per hour and uses stealth materials to reduce its radar cross-section (detection signal). The “Hunter’s” first flight was on August 3, 2019. Reportedly, as part of the flight test program, the first prototype of the “Hunter” has begun weapons testing: including test flights with a functional simulator carrying air-to-air missiles, and bombing ground targets at the Ashuluk test range. Currently, the Novosibirsk Chkalov Aircraft Plant is building three more “Hunter” UAV prototypes. Russia has completed combat formation flights of its multi-role fifth-generation Su-57 fighter jets and heavy “Hunter” reconnaissance and combat drones. These drones will be organized into multiple air regiments, likely joining Su-57 air regiments. The plan is for 2-3 Su-57 squadrons to each have a drone squadron, operating together and employing new strategies and artificial intelligence elements. The UK also plans to enable a single manned aircraft to simultaneously command five drones, while France plans to achieve mixed formation operations of Rafale fighter jets and Neuron drones.

The use of drones for military reconnaissance began in the 1960s and has been widely applied in various wars. During the Vietnam War, the US military deployed over 3,000 drone sorties for reconnaissance, with over 1,000 failing to return safely and disappearing without a trace. In the Gulf War, multinational forces deployed drones day and night to reconnoiter Iraqi frontline positions, providing real-time imagery and guiding ground troops to destroy Iraqi positions. In the Bosnian War, the US military used Predator drones to monitor the withdrawal of Serbian heavy weapons from Sarajevo and provided a wealth of target data for aircraft participating in airstrikes. In the Kosovo War, the US military deployed over 100 drones for battlefield reconnaissance and surveillance, contributing significantly to the 78-day air campaign. In the US operations against the Taliban, the US military used unmanned attack aircraft, carrying weapons, for the first time in actual combat. On September 14, 2019, after an attack on a Saudi Aramco oil company’s “world’s largest oil processing facility” and oil field, the Houthi rebels in Yemen claimed responsibility, stating they used 10 drones to attack the facility. On January 3, 2020, Qassem Soleimani, commander of the Quds Force of Iran’s Islamic Revolutionary Guard Corps, was killed in a US drone strike on Baghdad International Airport in the early morning. In late 2020, drones played a significant role in the conflict between Armenia and Azerbaijan in Nagorno-Karabakh. Many military experts were particularly impressed by the videos released by the Azerbaijani Ministry of Defense showing TB-2 “Standard” drones, recently purchased from Turkey, and Harop suicide drones, purchased from Israel, attacking Armenian armored vehicles, artillery, cars, and even infantry positions. While the videos clearly show the targets destroyed by the drones, the visual impact of the attacks was undeniably striking. The localized conflicts that occurred in the Middle East and the South Caucasus last December demonstrate the growing role of drones. No wonder some military strategists have even predicted that the 21st century will be the “golden age” for drone development, with drones inevitably replacing manned fighter jets and becoming the “protagonists of the battlefield” in the 21st century.

It can be predicted that future wars will inevitably see unmanned land, sea and air weapons replacing soldiers in performing high-risk missions, and the future battlefield will inevitably be a joint operation combining “human” and “machine”.

Combat-driven training means building an army based on how battles are fought. Future military equipment, whether tanks, robots, or drones, will likely take many forms. Future military personnel must be proficient in intelligent technologies, big data applications, and cloud computing, and master the programming methods for controlling intelligent robots and drones. The future army will inevitably be a “human-machine” integrated force, establishing “human-machine” integrated platoons, companies, combat simulation centers, adversary units, special forces, intelligent command headquarters, and unmanned battalions, regiments, and brigades. At that time, military commanders may have one human and one robot as assistants or deputies. Platoon and company commanders will gradually be replaced by robots, and robots will gradually transition from human control to autonomous decision-making or mind control via human brain cells. As early as the 2014 Brazil World Cup, a paralyzed teenager wearing a “mechanical exoskeleton armor” kicked the first ball through mind control. Today, the technology of mind control over objects or experimental animals is becoming increasingly sophisticated.

In future warfare, it will become possible for a small number of soldiers to lead a massive swarm of unmanned robots, such as bees, ants, or schools of fish, to carry out combat missions. Through thought-based group control, soldiers’ mission comprehension and battlefield control capabilities can be greatly enhanced, enabling efficient identification of friend or foe, remote real-time command, intelligent mission planning, and efficient autonomous collaboration. The Russian Foundation for Future Research states that they have mastered brain-computer interface technology for controlling machines through thought. Previously, British researchers developed a brain-computer interface device for controlling a spacecraft simulator; when worn on a test subject, it successfully controlled the flight of a model spacecraft. However, there is still a long way to go before soldiers can effectively control complex unmanned combat swarms using this technology. Military camps may also see further changes. Troop management may involve one or a few military commanders leading teams of multiple or even dozens of intelligent robots with different tasks to complete tasks previously performed manually. Alternatively, military training may involve a single military commander in a command and control center, using video to control all intelligent robots in the training field for adversarial training, or remotely controlling robot commanders to issue new training instructions, adjust mission deployments, and change training grounds in real time.

現代國語:

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訓練軍隊應對未來戰爭的原則是軍事戰略縱觀歷史的根本信條。一支不研究和預測戰爭的軍隊是愚蠢的軍隊,注定在戰爭爆發時失敗。 迄今為止,世界經歷了四次重大軍事變革:第一次是從主要使用木製和石製武器轉向主要使用金屬武器;第二次是從主要使用冷兵器(金屬武器)轉向主要使用火器(火藥武器);第三次是從火器轉向機械化武器;第四次發生在1990年海灣戰爭之後,戰爭從主要使用機械化武器化為使用機械化武器轉型,從主要使用機械化武器轉型為機械化武器化從主要使用機械化武器到了主要使用機械化武器轉型,從主要使用機械化武器化向武器化,從主要使用機械化武器轉變為從主要使用機械化武器轉型,從主要使用機械化武器轉向了主要使用機械化武器轉變為主要使用機械化武器。 第四次軍事革命,也被學術界稱為新軍事革命,指的是世界主要軍事強國在資訊科技、網路技術、精確導引技術、航空航天技術、新能源技術、生物技術和隱身技術等領域展開全面競爭。這場競爭如今已演變為對大數據、雲端運算和智慧機器人領域優勢的爭奪,旨在打造現實版的「鋼鐵人」、「蝙蝠俠」和「終結者」。這場革命正積極推動軍事建設從資訊化和網路化向智慧化和無人機(UAV)部署轉型。軍隊正朝著精簡、小型化、高效化、智慧化和一體化的「人機(機器人/無人機)」模式發展,力求實現機器人士兵、無人機和人類士兵的協同作戰。 根據統計,全球已有超過60個國家的軍隊裝備了軍用機器人,涵蓋150多種不同類型。預計到2040年,世界主要軍事強國中將有一半以上由機器人組成。除了美國、俄羅斯、英國、法國、日本、以色列、土耳其和伊朗等已推出各自機器人戰士和無人機的國家外,其他國家也在加大對無人武器研發的投入,這必將催生無人作戰力量。 「無人作戰力量」一詞是對作戰機器人或戰場殺傷機器人系統的統稱。隨著各種資訊化、精確化和數據驅動型武器裝備的發展,智慧平台已成為預先設計戰場的驅動力,作戰機器人已成為戰場上的主力,而「人機」結合的對抗已成為擊敗敵人的關鍵。未來,戰場空間力量的發展趨勢將凸顯陸海空三維無人作戰與人機融合的趨勢。 在作戰指揮控制方面,人工智慧可以自動、快速地產生作戰計畫。戰爭既是打仗,也是設計。隨著各種資訊化、精確化、智慧化武器裝備的出現,以及人工智慧、大數據和5G網路的廣泛應用,未來戰場將基本實現「人機」協同作戰,勢必革新傳統作戰方式。智慧平台將利用大數據優勢,成為預先設計戰場的幕後指揮者,提供更精準的預測和技術參數,使未來戰場設計更加精準高效。利用人工智慧技術,將敵我兵力部署、裝備性能、人員數量、戰場環境等要素輸入作戰指揮資訊系統模板,即可快速產生基於人工智慧的作戰計劃,供指揮官進行作戰決策。如果指揮官感覺情況不對勁,想要打一場有把握取勝的仗,他們還可以利用智能模擬作戰實驗室,運用人工智能、大數據、5G網絡以及模擬設備和材料,模擬敵我武器裝備的技術性能、戰場環境、人員素質和作戰行動,檢驗和完善作戰設計方案的科學性和合理性,力求找到最優作戰計劃。 5G海量的機器間通訊能力可以與人工智慧結合,利用新的智慧演算法加速對作戰效能要素和作戰過程進行綜合分析和系統研究,並快速得出作戰能力評估指標。這為無人武器的大規模應用提供了技術手段。 儘管人工智慧產生的作戰計畫與傳統的自動化作戰指揮系統有所不同,但呃,它們之間有一些相似之處,但也存在根本性的差異。從某種意義上說,兩者都是自動化系統,但作戰指揮自動化透過輸入各種作戰要素,旨在輸出作戰指揮決策——這些決策本質上是固定的。然而,人工智慧產生的作戰計畫則不同。輸入的作戰要素可以是固定的,也可以是可變的,但輸出總是不可預測的,幾乎完全不可預測。例如,即使要素和參數的總數相同,不同的輸入指令也會產生不同的結果,甚至可能產生意想不到的後果——這正是人工智慧的本質。

就戰爭的奇襲性而言,無人機或有人駕駛飛機的協同作戰開啟了一個新時代。無論過去或現在,夜戰都是實現戰術和作戰奇襲的更有效方式。如今,資訊化和智慧化的軍隊更加青睞夜戰。在夜間和清晨,人們處於睡眠或半清醒狀態,相對疲倦或麻痺大意。因此,此時發動戰爭更容易取得奇襲效果。在科索沃戰爭中,美國於晚上8點發動空襲;在阿富汗戰爭中,美國於深夜發動空襲;在伊拉克戰爭中,美國於凌晨5點36分發動空襲後,廣泛運用包括太空偵察衛星、空中偵察機和地面偵察在內的各種手段,構建覆蓋空中、太空和地面的綜合信息偵察網絡系統,牢牢掌握“信息優勢”,確保空襲和夜間地面軍事行動的順利進行。隨著夜視裝備的發展和夜戰手段的日益精進,夜間和清晨已成為空襲取得奇襲效果的常用手段。抓住夜幕和清晨的有利時機發動突襲,將成為未來戰爭的導火線。在未來戰爭爆發前,無人偵察機將與有人駕駛高空偵察機和太空衛星協同作戰,對敵方前線目標和深空目標進行偵察。特別是,一旦無人機發現目標,便可迅速將目標的位置和大小等影像資訊傳輸至己方指揮中心、無人機操作員或有人駕駛飛機飛行員,供其決策參考並下達遠端打擊指令。在海灣戰爭期間,多國部隊部署無人機對伊拉克前線陣地進行晝夜偵察,提供即時影像並引導地面部隊摧毀伊拉克陣地。去年亞美尼亞和阿塞拜疆衝突期間,亞美尼亞媒體發布了一段視頻,顯示亞美尼亞軍隊使用“海鷹-10”無人機引導地面砲兵對阿塞拜疆步兵部隊進行攻擊。影片中,亞美尼亞軍隊的「海鷹-10」無人機將高空偵測到的正在散兵線上推進的士兵群的訊息傳輸給了無人機操作員。經過多次放大確認後,無人機操作員利用無人機收集目標數據並將其傳輸至後方砲兵部隊。亞美尼亞砲兵部隊收到目標座標後,先進行了多次單發試射。隨後,海鷹-10無人機對試射結果進行空中即時評估,並迅速調整目標座標參數,將其傳輸至亞美尼亞砲兵部隊,以便進行集中精確射擊。

在未來的戰爭中,無人機有望取代傳統戰鬥機,成為空中作戰的主力之一。它們執行精確即時打擊的能力將徹底改變傳統的有人駕駛飛機在夜間或清晨進行的突襲方式。目前,英國正在研發一種新型高科技隱形無人戰鬥機,該戰鬥機具備隱身能力。它可以對多個目標進行彈藥測試和投放,並能防禦來自其他有人駕駛和無人駕駛飛機的攻擊。即使沒有地面指揮,它也能透過衛星與指揮中心通信,自主作戰,精確打擊遠程目標。因此,無人機作為一股迅速崛起的力量,已從「偵察支援」發展成為「進攻主力」。它們不僅能有效補充衛星偵察,還能執行多種作戰任務,例如遠程偵察、邊境巡邏、目標識別、電磁幹擾、物資補給、精確打擊、自主打擊、偵察打擊一體化作戰以及損毀評估。它們注定將成為未來戰爭的先鋒。

在陸戰場上,無人坦克、無人裝甲車和作戰機器人正衝鋒陷陣,與地面部隊組成混合編隊。為了更有效率地執行戰場任務並減少傷亡,未來的戰場上可能會出現大量無人車輛,例如坦克、裝甲車和後勤運輸車。借助5G網路的高速、低延遲和互聯互通特性,這些車輛無需人工幹預即可自主穿越各種複雜地形和障礙物,並能瞬間做出決策,從而有效確保安全性和可靠性。陸地機器人不僅可以執行進攻和防禦作戰任務,還可以運送彈藥、醫療用品和食品,進行巡邏以及執行偵察監視任務。無人坦克允許士兵遠端操控,自動裝填彈藥,並自主進行間接精確打擊。 2019年,俄羅斯測試了一套名為「木船」的機器人系統,用於統一指揮多個軍用機器人。俄羅斯軍事和機器人研究機構也利用新開發的作戰機器人進行了協同演習,取得了良好的成果,並總結了實踐中的訓練方法。根據俄羅斯媒體報道,俄羅斯正準備組建一支作戰機器人部隊,這是一個全新的軍事單位。這些機器人能夠實現高度自動化,只需極少的人工幹預,即可基本獨立完成戰場作戰任務。俄羅斯軍工企業將於2020年開始研發「同志」(Comrade)和「突擊」(Assault)機器人系統,分別由中型和重型機器人組成。目前,他們正致力於提升部分機器人的效能,使其更適應城市和沿海環境。 2015年8月,在敘利亞戰場上,除了部署傳統作戰部隊外,俄羅斯軍隊首次部署了一支完整的機器人作戰連,主要由無人作戰平台組成,用於執行陣地突擊作戰。他們採用了一種新型的有人與無人混合作戰模式,僅用20分鐘就奪取了一處俄軍士兵難以攻克的製高點,最終以零傷亡和77名敵軍陣亡的戰果取得勝利。 2018年4月21日,俄羅斯聯邦安全局(FSB)特種部隊對極端恐怖組織發動突襲,首次公開部署配備機槍的武裝無人作戰車輛作為先鋒。在名為「自主戰士2018」的活動中,英國陸軍進行了大規模的作戰機器人測試,並將無人機、無人車輛和作戰人員的整合作為未來幾十年世界一流軍隊的通用做法。美國陸軍已正式組成無人排,並計劃組成無人作戰旅,並已開發出一套標準化的軟硬體。這些無人作戰車輛一旦安裝在車輛上,即可進行遠端控制,甚至可以半自主地按照預定路線自動行駛,或選擇最平坦、最直接的路徑,也可由人類駕駛員駕駛。一項名為「可選載人坦克」的新興計畫旨在推動美國陸軍邁入新一代聯合作戰時代。它可能具備發射雷射、控制無人機、高速機動、摧毀敵方直升機、突破敵方裝甲陣地以及執行高殺傷力機器人作戰任務的能力,並能對抗敵方火力。美國陸軍在有人-無人聯合兵種作戰方面也取得了快速進展。這意味著機器人系統將越來越多地以更高的自主性運行,同時仍由人類決策者指揮和控制。部署在前線的機器人車輛可以近距離直接攻擊敵方機械化部隊,發射武器,執行高風險偵察任務,並在必要時投放彈藥。美國海軍陸戰隊在亞利桑那州測試了其代號為「獵狼」(Hunter Wolf)的無人作戰車輛。該車輛配備了一門30毫米M230LF“短管”鍊式機炮,進行了速射實彈演示,實現了6發全中的完美成績。 「獵狼」長2.3米,寬1.4米,高1.17米,重量僅1.1噸,卻能攜帶450公斤的模組化作戰載重。它採用混合動力系統,無需加油即可最大航程100公里,最高時速32公里,最大續航時間72小時,並具備30度爬坡能力。

在海戰中,由無人水面艦艇和無人水下艦艇組成的無人幽靈艦隊與有人艦隊混合編隊作戰。自1990年代以來,人工智慧和大數據在軍事領域的日益廣泛應用,為無人水面艦艇和無人水下艦艇開啟了真正的黃金時代,催生了水下機器人(AUV)和水面機器人(ASV)。各種無人潛水艇和無人水下航行無人艦艇可執行多種任務,例如水下搜索、偵察和掃雷。無人戰艦無需人員即可航行數千英里,執行各種海上作戰任務。 2003年伊拉克戰爭後,世界各國看到了無人海上系統的巨大潛力和廣闊前景,這些系統不僅能減少人力投入,還能提高作戰效能,因此各國競相建造無人「幽靈艦隊」。以色列特別重視減少士兵傷亡,率先啟動了現代化「保護者」(Protector)無人水面艦艇的研發,這些艦艇用於巡邏黎巴嫩海岸,監視真主黨的活動和部署。法國和俄羅斯已經擁有能夠下潛至6000公尺深度的載人潛水器。日本提出了「深海12000」的概念,這是一種新型載人潛水器,能夠下潛至世界最深處。繼「未來海上航空加速日」活動之後,英國繼續推動「即插即用」型自主海上平台開發系統。該系統一旦整合到英國皇家海軍艦艇上,將簡化自動化和無人技術的取得和使用。

在空中戰場上,無人機和有人駕駛飛機混合編隊戰鬥。 2019年,全球約30個國家已研發出50多種類型的無人機,超過50個國家已部署無人機。主要類型包括:密碼無人機、多功能無人機、人工智慧無人機、長航時無人機、反導無人機、預警無人機、隱形無人機、微型無人機、空戰無人機、測繪無人機、空拍無人機、武裝無人機和僚機無人機。隨著人工智慧和大數據等先進技術在軍事領域的廣泛應用,無人機裝備的效能也不斷提升。它們將整合偵察、火力校正、監視、戰果評估、目標識別、攻擊導引、無線電中繼和對地攻擊等多種功能。它們能夠遠距離對敵進行電子乾擾和欺騙,並在必要時自主攻擊重要地面目標。未來的空中戰場將基本實現無人或人機(無人機)協同空襲,或自主無人機空襲,這將徹底革新傳統的空戰方式。未來,戰鬥機飛行員將在座艙內操控無人攻擊機或轟炸機,以規避敵方防空系統,而進攻部隊將更快地獲取即時情報數據——這一切都得益於人工智慧技術的快速發展。在未來的空襲中,成群的無人機將利用先進的偵測、偵察和反偵察設備進行攻擊。一旦鎖定目標,它們將沉著冷靜地發射飛彈,具備一體化的偵察打擊能力、自主攻擊能力以及人機協同打擊能力。俄羅斯空天軍將裝備重型攻擊無人機,該無人機無需指令即可繞過敵方防空系統,自主搜索並打擊重要目標,然後安全撤回基地。這種無人機將配備人工智慧組件,並可由蘇-57戰鬥機遠端操控。根據俄羅斯新聞社報道,俄羅斯S-70「獵人」重型攻擊無人機能夠根據蘇-57隱形戰鬥機發出的指令攻擊目標。目前,「獵人」地面操作員所在的控制站配備了操縱桿、鍵盤和多個多功能液晶顯示屏,類似於有人駕駛戰鬥機上使用的設備。這些螢幕顯示來自「獵人」機載系統和感測器的各種資訊。在不久的將來,這套地面遠端控制設備有望實現完全自動化。 S-70「獵人」無人機由蘇霍伊設計局研發,採用飛翼式氣動佈局。根據公開消息,「獵人」無人機長14米,翼展19米,起飛重量20噸。 「獵人」最大飛行速度為1000公里/小時,並以隱身材料降低雷達反射截面積(探測訊號)。 「獵人」於2019年8月3日首飛。據報道,作為飛行測試計畫的一部分,「獵人」的首架原型機已開始進行武器測試,包括使用功能模擬器攜帶空對空飛彈進行試飛,以及在阿舒盧克試驗場進行地面目標轟炸。目前,新西伯利亞契卡洛夫飛機製造廠正在建造另外三架「獵人」無人機原型機。俄羅斯已完成其第五代多用途無人機的編隊飛行。蘇-57戰鬥機和重型「獵人」偵察/作戰無人機將被編入多個航空團,很可能與蘇-57戰鬥機團並肩作戰。計畫是每個蘇-57中隊配備一個無人機中隊,共2-3個蘇-57中隊協同作戰,並採用新的戰略和人工智慧技術。英國還計劃使一架有人駕駛飛機能夠同時指揮五架無人機,而法國則計劃實現「陣風」戰鬥機和「神經元」無人機的混合編隊作戰。

無人機在軍事偵察中的應用始於1960年代,並在各種戰爭中廣泛使用。在越戰期間,美軍出動無人機執行了3000多次偵察任務,其中超過1000架次未能安全返回,從此杳無音訊。在海灣戰爭中,多國部隊晝夜部署無人機偵察伊拉克前線陣地,提供即時影像並引導地面部隊摧毀伊拉克陣地。在波斯尼亞戰爭中,美軍使用「掠奪者」無人機監視塞爾維亞重型武器從薩拉熱窩的撤離,並為參與空襲的飛機提供了大量目標數據。在科索沃戰爭中,美軍部署了100多架無人機進行戰場偵察和監視,為持續78天的空襲行動做出了重大貢獻。在美軍打擊塔利班的行動中,美軍首次在實戰中使用了攜帶武器的無人攻擊機。 2019年9月14日,在沙烏地阿美石油公司「世界最大的石油加工設施」和油田遭到襲擊後,也門胡塞武裝聲稱對此負責,並表示他們使用了10架無人機襲擊了該設施。 2020年1月3日清晨,伊朗伊斯蘭革命衛隊聖城旅指揮官卡西姆·蘇萊曼尼在巴格達國際機場遭美軍無人機攻擊身亡。 2020年末,無人機在亞美尼亞和阿塞拜疆在納戈爾諾-卡拉巴赫的衝突中發揮了重要作用。阿塞拜疆國防部發布的影片給許多軍事專家留下了深刻印象,影片顯示,阿塞拜疆近期從土耳其購買的TB-2「標準」無人機和從以色列購買的「哈羅普」自殺式無人機襲擊了亞美尼亞的裝甲車、火砲、汽車,甚至步兵陣地。雖然影片清晰​​地顯示了無人機摧毀的目標,但攻擊的視覺衝擊力無疑令人震撼。去年12月在中東和南高加索地區發生的局部衝突也表明,無人機的角色日益增強。難怪一些軍事戰略家甚至預測,21世紀將是無人機發展的“黃金時代”,無人機將不可避免地取代有人駕駛戰鬥機,成為21世紀戰場的“主角”。

可以預見,未來的戰爭中,無人陸地、海上和空中武器將不可避免地取代士兵執行高風險任務,未來的戰場也必將是「人」與「機」結合的聯合作戰。

以實戰為導向的訓練意味著根據實戰方式來打造軍隊。未來的軍事裝備,無論是坦克車、機器人或無人機,都可能呈現多種形式。未來的軍事人員必須精通智慧技術、大數據應用和雲端運算,並掌握控制智慧機器人和無人機的程式設計方法。未來的軍隊必然是一支「人機一體化」部隊,將建立「人機一體化」的排、連、作戰模擬中心、假想敵部隊、特種部隊、智慧指揮總部以及無人營、團、旅。屆時,軍事指揮官可能會配備一名人類和一名機器人作為助手或副手。排長和連長將逐步被機器人取代,而機器人也將逐步從人類控制過渡到自主決策,甚至透過人類腦細胞進行意念控制。早在2014年巴西世界盃上,一位身穿「機械外骨骼裝甲」的癱瘓少年就透過意念控制踢出了第一球。如今,對物體或實驗動物進行意念控制的技術正變得越來越成熟。

在未來的戰爭中,少數士兵將有可能指揮龐大的無人機人群,例如蜜蜂、螞蟻或魚群,以執行作戰任務。透過基於意念的群體控制,士兵的任務理解能力和戰場控制能力可以大大提升,從而實現敵我識別、遠程即時指揮、智慧任務規劃和高效自主協作。俄羅斯未來研究基金會聲稱,他們已經掌握了透過意念控制機器的腦機介面技術。先前,英國研究人員也開發了一種用於控制機器的腦機介面設備。該設備在航天器模擬器上進行了操控;當佩戴在測試對象身上時,它成功控制了模型航天器的飛行。然而,士兵要利用這項技術有效控制複雜的無人作戰集群,還有很長的路要走。軍事營地也可能迎來進一步的變革。部隊管理可能由一名或幾名指揮官帶領由多個甚至數十個智慧機器人組成的團隊,這些機器人承擔不同的任務,完成以前由人工完成的工作。另一種可能性是,軍事訓練可能由一名指揮官在指揮控制中心,透過視訊控制訓練場上的所有智慧機器人進行對抗訓練,或遠端控制機器人指揮官,即時發布新的訓練指令、調整任務部署和更改訓練場地。

中國原創軍事資源:http://www.81.cn/bq_208581/jdt_208582/180080804830.html

Chinese Military Forum | Artificial Intelligence Empowers Synthetic Training Improving Quality & Efficiency

中國軍事論壇 | 人工智慧賦能合成訓練,提升品質與效率

現代英語:

The form of warfare determines the form of training. Currently, the widespread application of artificial intelligence technology will reshape the form of warfare and combat patterns, and trigger profound changes in military training. As an important part of the organizational structure of the new military training system, combined arms training urgently needs to be infused with an “intelligent core” of artificial intelligence, so as to better play its pivotal role in the new military training system, realize the transformation from “formal integration” to “spiritual integration,” and from “elemental coordination” to “intelligent leadership,” and promote the continuous advancement of combined arms training in the new era to higher quality and higher level.

Breaking the deadlock: Driving a change in training logic

Artificial intelligence empowers synthetic training not only as an “efficiency enhancement tool” to improve training effectiveness, but also leads to changes in the connotation, extension, mechanism, and standard requirements of synthetic training.

Achieving intelligent coupling involves a shift in the logic of convergence. Overcoming division through unity and disunity through cohesion are crucial battlefield principles. The key to combined arms training is “unity.” Artificial intelligence empowers combined arms training to better adapt to the collaborative needs of intelligent warfare, making it crucial for creating a “chemical reaction” in operational coordination. The training focuses on deeply integrating human creativity and value judgment with the computing power and intelligence of machines, forming a cognitive advantage at a higher dimension, and achieving a highly integrated, flexible, and intelligently coupled training system. Manned-unmanned collaborative training is a typical example of deeply integrating manned combat forces with unmanned combat systems possessing “intelligent brains,” pursuing minimal casualties and maximum operational efficiency.

Achieving an iterative logical transformation into a closed-loop system. Traditional training is limited by physical conditions, resulting in high trial-and-error costs and long iteration cycles. By leveraging artificial intelligence to create a “digital twin” training environment, through virtual-real interaction and iterative feedback in parallel systems, synthetic training can shift towards a process of continuous exploration, trial-and-error optimization, forming a new training closed loop. Training at different levels can be implemented simultaneously, and thousands of tactics can be tested and optimized in parallel in virtual space at low cost and high speed. The various elements of overall combat capability can be generated almost independently without regard to sequence. At the same time, the generation of combat capabilities exhibits certain characteristics of distribution, synchronicity, integration, and nonlinearity, significantly compressing the traditional training cycle, accelerating the synchronous generation of combat capabilities across levels, and further expanding the iteration of combat capabilities to “intra-domain foundation, cross-domain collaboration, and full-domain integration”.

Extending the value logic of intelligent emergence. Traditional training cannot pre-plan all possible interactions, nor can it easily generate new tactics and collaborative modes that go beyond pre-set plans. This dilemma is difficult to overcome when facing the demands of intelligent warfare. However, artificial intelligence is quietly changing this model, transforming the value of the training ground from simulating past wars to exploring the possibilities of future wars. Artificial intelligence empowers synthetic training, injecting it with the underlying driving force to generate “intelligent emergence.” For example, game-like confrontations with intelligent opposing forces force trainees to break out of conventional thinking frameworks, potentially leading to previously unthinkable, counterintuitive tactical combinations. The purpose of synthetic training is not only to execute known tactics, but also to hone the ability to innovate methods and update strategies in adversarial environments.

Reconstruction: Shaping Synthetic Training Patterns

Synthetic training incorporating artificial intelligence is gradually evolving into a new training model that emphasizes combat-oriented organization, focuses on enhancing intelligence and integration, shifts towards distributed autonomy, and is geared towards dynamic battlefields.

The training focuses on combat-oriented grouping. Today’s combined arms training features more diverse training subjects, more varied force compositions, and higher capability requirements. The training emphasizes combat-oriented grouping, focusing on mission-driven consistency between training and combat, and is characterized by modularity, innovation, and scalability. Artificial intelligence, acting as a “dispatch center,” can assess the status of combat units based on the battlefield situation, quickly generate optimal force grouping plans, allocate relevant elements as needed, integrate new domain and new quality forces, and practice how to quickly aggregate and disperse forces to form flexible “mission-customized” combined arms groups. This provides the system with plug-and-play capability modules that can be dynamically reconstructed, efficiently linked, and adaptively adjusted like building blocks.

Training content leans towards enhancing intelligence and integration. Traditional training focuses more on assessing whether coordinated actions are completed according to plan, time limits, and standards. In intelligent warfare, humans and intelligent systems together form the basic combat components, exerting combat effectiveness through their functional division and deep integration. Therefore, the focus of new-era integrated training should also pay more attention to improving human-machine integration capabilities. In the past, training content based on human-to-human collaboration—including technology upgrades, experience-based training, and self-awareness training—has become less effective. Training content that enhances intelligence and integration is gradually becoming the key to integrated training. In tactical coordination training, trainees need to master how to collaborate and interact efficiently with artificial intelligence systems, how to use artificial intelligence to reorganize collaborative relationships, close the kill chain, coordinate joint troop actions, and achieve “combined punches”.

Training methods are shifting towards distributed and autonomous approaches. The changes brought about by artificial intelligence to combined arms training are primarily reflected in training methods. This involves not only mastering coordinated operations and solidifying the foundation of collaboration, but also in how to innovatively lead the evolution of combat systems. Distributed training, relying on AI technology, supports simultaneous, remote joint training between different combat units under the same combat background, scenario, and battlefield situation, improving training effectiveness. Autonomous training, employing a “human-outside-the-loop” approach, hones trainees’ ability to handle contingencies and act autonomously. Through feedback and self-adjustment, it promotes autonomous iterative upgrades. Conducting adversarial training breaks through the limitations of learning to fight from experience in the past. It introduces an AI-powered “blue team” to “learn” to fight in a simulated complex battlefield environment, adding random, extreme, and highly harassed scenarios.

Training scenarios are geared towards dynamic battlefields. Traditional training scenarios are mostly “pre-set scripts” designed around “established capabilities” and “known threats,” unable to break free from limited cognition and established thinking patterns. Artificial intelligence empowers synthetic training, transforming it into a “dynamic game system” targeting “unknown capabilities” and “emerging threats,” making it more “imaginative.” Based on training objectives, artificial intelligence autonomously generates logical, multi-domain, and multi-dimensional virtual combat scenarios. Through repeated practice in such highly complex and uncertain environments, trainees are more likely to develop new understandings of the future battlefield.

Exploration: Prospective Synthetic Training Path

Artificial intelligence-enabled synthetic training is an iterative evolutionary process. Looking ahead at its development path, the aim is to transcend developmental limitations and narrow-minded thinking, directly addressing “multi-agent game theory” and “digital twin training grounds,” thereby achieving multi-dimensional and systematic advancement.

Build a comprehensive training foundation. Based on digital twins and intelligent technologies, create a comprehensive training environment to achieve intelligent interaction between people, equipment, and environment. This will enable all training combat units to become dynamically adjustable “intelligent agents,” conduct cross-domain training, improve the command, decision-making, and adaptive coordination capabilities of human-machine hybrid intelligence, and incubate new tactics and formation patterns in a realistic battlefield environment.

Deploy an intelligent blue force system. Build an algorithmic adversary with autonomous evolution capabilities and dynamic game theory thinking, shifting training from “adapting to the known” to “coping with the unknown.” Through deep reinforcement learning and game theory models, the intelligent blue force can not only learn known tactical experiences but also autonomously generate diverse tactics based on real-time situations. Furthermore, it can gain insights into the opponent’s behavioral patterns during interactions, prompting the development of real and effective strategies in dynamic confrontations, and honing the unit’s tactical innovation and human-machine collaboration capabilities through continuous high-intelligence confrontations.

Innovate integrated training models. New-era combined arms training demands innovation-driven, technology-enabled approaches, requiring bold exploration and willingness to experiment. This necessitates seamlessly integrating testing grounds, training grounds, and battlefields, and innovating an integrated training model encompassing operational testing institutions, training institutions, and troops. Trainers are not merely simple technology providers and supporters, but rather embedded as training designers, process analysts, and evaluators within the training process. This allows for a better understanding and methodological revolution in training, validating new technologies, tactics, and formations in combined arms training, exploring future combat winning mechanisms, and simultaneously using data from real-world training to optimize artificial intelligence models, forming an integrated and interactive closed loop that truly integrates training with real-world application.

現代國語:

戰爭形式決定訓練形式。目前,人工智慧技術的廣泛應用將重塑戰爭形式和作戰模式,並引發軍事訓練的深刻變革。作為新軍事訓練體系組織結構的重要組成部分,諸兵種合成訓練亟需注入人工智能的“智能核心”,以更好地發揮其在新軍事訓練體系中的關鍵作用,實現從“形式融合”到“精神融合”、“要素協調”到“智能領導”的轉變,推動新時代諸兵種合成訓練不斷邁向更高水平、更高質量的發展。

打破僵局:驅動訓練邏輯的變革

人工智慧賦予合成訓練的權力不僅在於將其作為提升訓練效果的“效率增強工具”,更在於引發合成訓練在內涵、延伸、機制和標準要求等方面的變革。

實現智慧耦合意味著融合邏輯的轉變。以團結化解分裂,以凝聚力化解紛爭,是戰場上至關重要的原則。聯合兵種訓練的關鍵在於「團結」。人工智慧賦能聯合兵種訓練,使其更適應智慧戰爭的協同作戰需求,從而在作戰協調中產生「化學反應」。該訓練著重於將人類的創造力和價值判斷與機器的運算能力和智慧深度融合,形成更高維度的認知優勢,並建構高度整合、靈活且智慧耦合的訓練體系。有人-無人協同訓練是將有人作戰部隊與擁有「智慧大腦」的無人作戰系統深度融合的典型例證,旨在最大限度地減少傷亡並提高作戰效率。

實現迭代邏輯轉換,形成閉環系統。傳統訓練受限於物理條件,導致試誤成本高且迭代週期長。透過利用人工智慧創造「數位孿生」訓練環境,在平行系統中實現虛擬實境互動和迭代回饋,合成訓練可以轉向持續探索、試誤優化的過程,形成新的訓練閉環。不同層級的訓練可以同時進行,數千種戰術可以在虛擬空間中以低成本、高速度並行測試和最佳化。整體作戰能力的各要素幾乎可以獨立生成,無需考慮順序。同時,作戰能力的生成呈現出一定的分佈性、同步性、整合性和非線性特徵,顯著壓縮了傳統訓練週期,加速了跨層級作戰能力的同步生成,並將作戰能力的迭代進一步擴展至「域內基礎、跨域協同、全局融合」。

拓展智能湧現的價值邏輯。傳統訓練無法預先規劃所有可能的交互,也難以產生超越預設計劃的新戰術和協同模式。面對智慧戰爭的需求,這一困境難以克服。然而,人工智慧正在悄悄改變這個模式,將訓練場的價值從模擬過去的戰爭轉變為探索未來戰爭的可能性。人工智慧賦能合成訓練,為其註入了產生「智慧湧現」的內在驅動力。例如,與智慧敵軍進行遊戲式的對抗,迫使受訓人員打破傳統的思維框架,可能催生出以前難以想像、違反直覺的戰術組合。合成訓練的目的不僅在於執行已知的戰術,更在於磨練在對抗環境中創新方法和更新策略的能力。

重構:塑造合成訓練模式

融合人工智慧的合成訓練正逐步演變為一種新的訓練模式,強調以作戰為導向的組織,專注於提升情報和協同作戰能力,轉向分散式自主作戰,並適應動態戰場環境。

訓練重點在於以作戰為導向的編隊。如今的聯合兵種訓練具有更多樣化的訓練科目、更豐富的兵力構成以及更高的能力要求。此訓練強調以戰鬥為導向的分組,專注於訓練與實戰之間任務驅動的一致性,並以模組化、創新性和可擴展性為特點。人工智慧作為「調度器」發揮作用。「指揮中心」能夠根據戰場態勢評估作戰單位的狀態,快速生成最優兵力編組方案,根據需要調配相關要素,整合新領域和新素質的部隊,並演練如何快速集結和分散兵力,形成靈活的「任務定制」合成兵種群。這為系統提供了即插即用的能力模組,可以像積木一樣動態重構、高效連接和自適應調整。

訓練內容傾向於增強智慧化和一體化能力。傳統訓練更著重於評估協同行動是否按計劃、按時、按標準完成。在智慧戰中,人和智慧系統共同構成基本的作戰要素,透過功能分工和深度融合發揮作戰效能。因此,新時代一體化訓練的重點也應更重視提升人機融合能力。過去基於人際協作的訓練內容——包括技術升級、經驗訓練和自我意識訓練——效果已下降。增強智慧化和一體化能力的訓練內容正逐漸成為一體化訓練的關鍵。在戰術協調方面,在訓練中,受訓人員需要掌握如何與人工智慧系統高效協作和互動,如何利用人工智慧重組協作關係,完善殺傷鏈,協調聯合部隊行動,並實現「組合打擊」。

訓練方法正朝著分散式和自主化方向發展。人工智慧為聯合兵種訓練帶來的變革主要體現在訓練方法上。這不僅包括掌握協同作戰和鞏固協作基礎,還包括如何創新地引領作戰系統演進。分散式訓練依賴人工智慧技術,支援不同作戰單位在相同作戰背景、場景和戰場情勢下進行同步遠程聯合訓練,進而提高訓練效率。自主訓練採用「人外環」的方式,磨練受訓人員處理突發事件和自主行動的能力。透過回饋和自我調整,促進自主迭代升級。對抗訓練突破了以往從經驗中學習作戰的局限性,引入人工智慧驅動的「藍隊」進行「學習」。在模擬的複雜戰場環境中作戰,並加入隨機、極端和高度騷擾的場景。

訓練場景面向動態戰場。傳統的訓練場景大多是圍繞著“既有能力”和“已知威脅”設計的“預設腳本”,無法突破認知限制和既定思維模式的束縛。人工智慧賦能合成訓練,將其轉變為針對“未知能力”和“新興威脅”的“動態博弈系統”,使其更具“想像力”。基於訓練目標,人工智慧自主產生邏輯嚴密、多域、多維度的虛擬作戰場景。透過在高度複雜和不確定的環境中反覆練習,受訓人員更有可能對未來的戰場形成新的理解。

探索:合成訓練的未來路徑

人工智慧賦能的合成訓練是一個迭代演進的過程。展望其發展路徑,目標是超越發展局限和狹隘思維,直接面向“多智能體博弈論”和“數位孿生訓練場”,從而實現…多維度、系統性推進。

建構綜合訓練基礎。基於數位孿生與智慧技術,創造綜合訓練環境,實現人、裝備、環境的智慧互動。這將使所有訓練作戰單位成為動態可調的“智能體”,開展跨域訓練,提升人機混合智能的指揮、決策和自適應協調能力,並在真實戰場環境下孵化新的戰術和陣型。

部署智慧藍軍系統。建構具備自主演化能力和動態博弈論思維的演算法對手,將訓練重心從「適應已知」轉向「應對未知」。透過深度強化學習和賽局理論模型,智慧藍軍不僅能夠學習已知的戰術經驗,還能根據即時情況自主生成多樣化的戰術。此外,它還能洞察對手在互動中的行為模式,進而促進戰術的演進。在動態對抗中製定切實有效的戰略,並透過持續的高智慧對抗來磨練部隊的戰術創新能力和人機協作能力。

創新一體化訓練模式。新時代的聯合兵種訓練需要創新驅動、技術賦能的方法,需要大膽探索和勇於嘗試。這就要求無縫整合試驗場、訓練場和戰場,並創新涵蓋作戰測試機構、訓練機構和部隊的一體化訓練模式。教官不再只是技術提供者和支持者,而是作為訓練設計者、流程分析師和評估者融入訓練過程中。這有助於更好地理解訓練方法並進行方法論上的革新,驗證聯合兵種訓練中的新技術、戰術和陣型,探索未來作戰的製勝機制,並同時利用來自真實世界訓練的數據來優化人工智慧模型,從而形成一個真正將訓練與實際應用相結合的整合式互動式閉環。

來源:解放軍報 作者:聶曉麗 趙澤夏 責任編輯:王一亙 2026-01-13 07:xx:xx

聶曉麗 趙澤夏

中國原創軍事資源:http://www.mod.gov.cn/gfbw/jmsd/164838781898.html

China’s Forward-looking Intelligent Combat System Provides Chinese Military a “Smart” Advantage

中國前瞻性的智慧作戰系統為中國軍隊提供了「智慧」優勢

現代英語:

The evolution of warfare and combat styles is inextricably linked to profound changes in combat systems. The “intelligence” of intelligent combat systems lies not merely in the accumulation of technologies, but more importantly in the reconstruction of the paths for generating and releasing combat power, enabling leaps in combat effectiveness and serving as a key fulcrum for achieving victory in future wars. A deep understanding and forward-looking construction of the “intelligent” advantages of intelligent combat systems has become an essential requirement for winning intelligent warfare.

Survival advantages of elastic redundancy

The survival of operational elements is fundamental to victory in combat. Intelligent combat systems, through distributed and flexible deployment, modular functional reconfiguration, and autonomous damage recovery, have formed a resilient survival mode to cope with high-intensity confrontation and uncertainty.

Heterogeneous and distributed global deployment. Heterogeneity reflects the degree of aggregation of different capabilities on the same platform, while distribution reflects the degree of distribution of the same capability on different platforms. Intelligent combat systems enhance the diversity of platform capabilities through heterogeneity. For example, new combat aircraft can serve as multi-functional integrated platforms with sensing, command and control, relay, and strike capabilities. By distributing combat functions to different platforms, large-scale, low-cost global deployment can be achieved. For instance, the same combat function can be assigned to multiple platforms and systems such as UAVs and loitering munitions. With the heterogeneous dispersion and matrix cross-linking of intelligent nodes, continuous pressure can be formed everywhere and in all directions in physical space, while rapid aggregation in key directions can be achieved. This unifies global elasticity and dynamic real-time optimization, maximizing functional distribution and effectiveness release to cope with the uncertainties of intelligent combat.

Functional restructuring through modular combination. The intelligent combat system, employing a flexible paradigm of software-defined, task-oriented invocation, and modular reconfiguration, deconstructs functions fixed to specific equipment into standardized, interoperable hardware and software modules. During combat, based on rapidly changing battlefield demands, these modules can be quickly and flexibly loaded and combined online through a unified interface and open architecture, achieving non-linear functional combinations and flexible capability reshaping. This plug-and-play, on-demand generation model unlocks unlimited functional potential within a limited physical scale, realizing a shift from “using whatever weapons are available to fight” to “generating the appropriate capabilities for the specific battle,” fundamentally enhancing the adaptability and mission flexibility of the combat system.

Self-healing resilience. The advantage of an intelligent combat system lies not in its absolute invulnerability, but in its self-healing resilience—the ability to detect damage and reconstruct immediately upon interruption. When some nodes fail due to combat damage or interference, the system autonomously and rapidly diagnoses the damage based on preset functions and path redundancy rules. It then mobilizes nearby healthy nodes to take over the mission or activates backup communication paths to rebuild connections, propelling the system to quickly transition to a new stable state. This inherent elastic redundancy allows the system to maintain core functions and reconstruct the combat network even after enduring continuous attacks, minimizing the impact of combat damage on overall combat effectiveness.

The cognitive advantage of agile penetration

Cognitive advantage is key to gaining the initiative in battlefield information and achieving decisive victory. Its essence lies in breaking through the barriers of “information fog” and the constraints of “decision anxiety” through the deep integration of intelligent algorithms and advanced sensors, and realizing a leap from passive perception to proactive cognition.

Resilient communication capable of adapting to changing circumstances. Resilient communication refers to the ability of communication systems to detect interference in real time and dynamically reconfigure links in highly contested and complex electromagnetic environments to maintain the continuity and stability of command and control. Intelligent combat systems, relying on technologies such as cognitive radio, achieve on-demand allocation of communication resources, intelligent optimization of transmission paths, and autonomous reconfiguration of network topology, enabling them to “penetrate gaps” in complex electromagnetic environments and flexibly acquire communication “windows.” This resilience—able to maintain communication even amidst interference and resume operations even after interruptions—ensures the continuity of command and control relationships in extremely harsh electromagnetic environments, providing a reliable communication line for system cognitive activities.

The organic integration of multi-modal information. Multi-modal integration refers to the process of extracting consistency from diverse and heterogeneous information to form a high-value battlefield situation. The intelligent combat system, based on intelligent algorithms, performs cross-modal alignment of data from different sources such as radar, optoelectronics, reconnaissance, and cyber warfare. It automatically extracts enemy deployment, action patterns, and tactical intentions from massive and fragmented intelligence, achieving heterogeneous complementarity and cross-verification. This drives a qualitative leap from data redundancy to accurate intelligence, thereby providing commanders with a comprehensive and reliable battlefield cognitive map, clearing away the “fog of war,” and reaching the core of the situation.

Human-machine interaction achieves seamless intent. Intent-based intent aims to bridge the semantic gap between human commanders and intelligent combat systems, enabling precise and lossless conversion from natural language commands to machine-executable tasks. Intelligent combat systems utilize technologies such as natural language processing and knowledge graphs to construct an intelligent interaction engine with natural language understanding and logical reasoning capabilities. This engine automatically decomposes the commander’s general operational intent into task lists, constraints, and evaluation criteria, generating machine-understandable and executable tactical instructions and action sequences, which are then precisely distributed to the corresponding combat units, directly driving their execution. This “what is thought is what is directed, what is directed is what is attacked” command model significantly reduces the understanding and communication cycle in the traditional command chain, enabling deep integration of human and machine intelligence at the decision-making level and achieving a leap in command effectiveness.

Synergistic advantages of autonomous adaptation

Synergistic advantages are a multiplier for unleashing the effectiveness of system-of-systems warfare. The synergy of intelligent combat systems transcends programmed pre-setup, manifesting as the self-organizing and adaptive synchronization and cooperation of cross-domain combat units under unified rules and common missions. Its essence is the embodiment of system intelligence at the operational level.

Spatiotemporal coordination constrained by rules. Spatiotemporal coordination refers to setting action boundaries and interaction rules for widely dispersed combat units within a unified spatiotemporal reference framework, ensuring their orderly cooperation in the physical domain. Under a unified operational rule framework, each unit of the intelligent combat system autonomously calculates its relative position and predicts its trajectory through intelligent algorithms, achieving time-domain calibration, spatial-domain integration, and frequency-domain nesting of different platforms. This ensures conflict-free path planning, interference-free spectrum use, and accident-free firepower application. This collaborative mechanism, which combines order and flexibility, avoids mutual interference while maintaining tactical flexibility, providing a spatiotemporal reference for combat operations in complex battlefield environments.

Task-driven logical coordination. Logical coordination refers to using combat missions as the underlying logic, autonomously decomposing tasks, allocating resources, and planning actions to achieve intelligent organization and scheduling. The intelligent combat system, based on task analysis, capability matching, and planning generation algorithms, automatically decomposes combat objectives into specific action sequences and intelligently schedules corresponding combat units to “dispatch orders.” Each intelligent node, based on its understanding of the overall mission, real-time situational awareness, and its own capabilities, autonomously decides on action plans through a multi-agent negotiation mechanism and dynamically negotiates and cooperates with relevant units to “accept orders.” This task-oriented command greatly liberates higher-level commanders, enabling the system to possess agility and flexibility in responding to emergencies and significantly improving its mission adaptability.

Target-aligned awareness collaboration. Awareness collaboration refers to the autonomous decision-making and actions of combat units based on a shared understanding of the target and environment, resulting in synergistic effects. Intelligent combat systems consist of systems or nodes with predictive and reasoning capabilities. Driven by operational objectives, they can anticipate the actions of friendly forces and the course of the battlefield, and through local perception and independent decision-making, conduct self-organized and self-inspired collaborative support. This efficiency-driven, unspoken consensus transcends communication constraints and pre-set procedures, enabling the system to demonstrate exceptional adaptability and creativity when facing powerful adversaries.

The evolutionary advantages of learning iteration

Evolutionary advantage is key to a combat system’s sustained competitiveness and ability to seize the initiative on the battlefield. Intelligent combat systems rely on real-time adversarial data to drive overall optimization, accelerate capability diffusion through cross-domain experience transfer, and foster disruptive tactics through virtual gaming environments, thereby achieving autonomous evolution and generational leaps in combat effectiveness during the adversarial process.

The evolution of a system built upon accumulated experience. Intelligent combat systems will gather perception, decision-making, and action data acquired from complex adversarial environments in real time to a knowledge hub. Leveraging advanced algorithms such as reinforcement learning, they will conduct in-depth analysis and mining, performing closed-loop evaluation and dynamic adjustment of system-level operational logic such as command processes, coordination rules, and resource allocation strategies. This will form reusable and verifiable structured knowledge units, enhancing the combat system’s understanding of its environment and its autonomous adaptability. This will enable the entire system to form a shared “collective memory,” achieving adaptive radiation from single-point intelligence to overall operational effectiveness, and ultimately achieving individual evolution that becomes “more refined with each battle.”

Cross-domain empowerment of knowledge transfer. The intelligent combat system, relying on a unified semantic space and feature alignment framework, can rapidly embed localized experiences extracted and summarized from a specific battlefield or domain into other combat domains or mission scenarios. This breaks down information barriers between combat units, enabling the lossless transformation and cross-domain application of combat experience. Essentially, it promotes the secure flow and synergistic effect of knowledge within the system, completing the sublimation and reconstruction from “concrete experience” to “abstract knowledge,” achieving “gains from one battle benefiting all domains,” and accelerating the synchronous evolution of combat capabilities across various domains. This not only significantly improves the overall learning efficiency of the combat system and avoids repeated trial and error, but also achieves the intensive enhancement and systematic inheritance of combat capabilities.

The disruptive potential of game theory and confrontation is emerging. Systemic intelligent game theory aims to break through the boundaries of human cognition, fostering disruptive combat capabilities that transcend traditional experience. Its essence lies in the proactive creation and self-transcendence of knowledge at the system level. By constructing a high-intensity, long-term, realistic “red-blue” adversarial environment in a digital twin battlefield, and utilizing generative adversarial networks and multi-agent reinforcement learning frameworks, intelligent combat systems can explore the unknown boundaries of the strategy space in continuous game development. Based on game theory and complex systems theory, the system can spontaneously form better strategies during adversarial evolution, leading to combat modes and organizational forms that transcend conventional cognition. This makes the intelligent combat system a “super think tank” capable of continuously producing disruptive tactics.

現代國語:

戰爭和作戰方式的演變與作戰系統的深刻變革密不可分。智慧作戰系統的「智慧」不僅在於技術的積累,更重要的是重構作戰能力生成與釋放路徑,從而實現作戰效能的飛躍,並成為未來戰爭取勝的關鍵支點。深入理解並前瞻性地建構智慧作戰系統的「智慧」優勢,已成為贏得智慧戰爭的必要條件。

彈性冗餘的生存優勢

作戰要素的生存是戰爭勝利的根本。智慧作戰系統透過分散式靈活部署、模組化功能重建和自主損傷恢復,形成了應對高強度對抗和不確定性的韌性生存模式。

異質分散式全球部署。異質性反映了不同能力在同一平台上的聚合程度,而分散式則反映了相同能力在不同平台上的分佈程度。智慧作戰系統透過異質性增強了平台能力的多樣性。例如,新型作戰飛機可以作為集感知、指揮控制、中繼和打擊能力於一體的多功能整合平台。透過將作戰功能分配到不同的平台,可以實現大規模、低成本的全球部署。例如,同一作戰功能可以分配給多個平台和系統,例如無人機和巡彈。借助智慧節點的異質分散和矩陣式交叉連接,可以在物理空間的各個方向形成持續的壓力,同時實現關鍵方向的快速聚合。這統一了全局彈性和動態即時最佳化,最大限度地提高功能分配和效能釋放,以應對智慧作戰的不確定性。

透過模組化組合進行功能重構。智慧作戰系統採用軟體定義、任務導向和模組化重構的靈活範式,將固定於特定設備的功能解構為標準化、可互通的硬體和軟體模組。在戰鬥中,基於瞬息萬變的戰場需求,這些模組可透過統一的介面和開放式架構,在線上快速靈活地載入和組合,實現非線性功能組合和靈活的能力重塑。這種即插即用、按需生成的模式,在有限的物理規模內釋放了無限的功能潛力,實現了從「使用任何可用武器作戰」到「為特定戰鬥生成合適的能力」的轉變,從根本上增強了作戰系統的適應性和任務靈活性。

自癒韌性。智慧作戰系統的優勢不在於其絕對的無懈可擊,而在於其自癒韌性——即在中斷發生後能夠立即檢測損傷並進行重建。當某些節點因戰鬥損傷或乾擾而失效時,系統會基於預設功能和路徑冗餘規則,自主快速地診斷損傷。然後,它會調動附近的健康節點接管任務,或啟動備用通訊路徑重建連接,從而使系統迅速過渡到新的穩定狀態。這種固有的彈性冗餘使系統即使在遭受持續攻擊後也能維持核心功能並重建作戰網絡,從而最大限度地降低戰鬥損傷對整體作戰效能的影響。

敏捷滲透的認知優勢

認知優勢是掌握戰場資訊主動權並取得決定性勝利的關鍵。其本質在於透過智慧演算法和先進感測器的深度融合,突破「資訊迷霧」的障礙和「決策焦慮」的束縛,實現從被動感知到主動認知的飛躍。

適應環境變化的彈性通訊。彈性通訊是指通訊系統在高度對抗且複雜的電磁環境中即時偵測幹擾並動態重配置鏈路,以維持指揮控制的連續性和穩定性的能力。智慧作戰系統依托認知無線電等技術,實現通訊資源的按需分配、傳輸路徑的智慧優化以及網路拓撲的自主重配置,使其能夠在複雜的電磁環境中「穿透縫隙”,靈活獲取通訊「視窗」。這種韌性-即使在…之中也能保持溝通即使中斷後也能進行幹擾並恢復操作-確保在極度惡劣的電磁環境下指揮控制關係的連續性,為系統認知活動提供可靠的通訊線路。

多模態訊息的有機融合。多模態融合是指從多樣化且異構的資訊中提取一致性,形成高價值的戰場態勢的過程。基於智慧演算法的智慧作戰系統,對雷達、光電、偵察和網路戰等不同來源的資料進行跨模態對齊。它能夠從海量且碎片化的情報中自動提取敵方部署、行動模式和戰術意圖,實現異質互補和交叉驗證。這實現了從數據冗餘到精準情報的質的飛躍,從而為指揮官提供全面可靠的戰場認知地圖,撥開“戰爭迷霧”,直擊戰局核心。

人機互動實現無縫意圖傳遞。基於意圖的意圖旨在彌合人類指揮官與智慧作戰系統之間的語義鴻溝,實現自然語言指令到機器可執行任務的精確無損轉換。智慧作戰系統利用自然語言處理和知識圖譜等技術建構具備自然語言理解和邏輯推理能力的智慧互動引擎。該引擎自動將指揮官的整體作戰意圖分解為任務清單、約束條件和評估標準,產生機器可理解和執行的戰術指令和行動序列,並將其精確地分發給相應的作戰單元,直接驅動其執行。這種「所想即所發,所發即所攻」的指揮模式顯著縮短了傳統指揮鏈中的理解和溝通週期,實現了決策層面的人機智能深度融合,從而大幅提升了指揮效能。

自主調適的協同優勢

協同優勢是釋放系統間作戰效能的倍增器。智慧作戰系統的協同作用超越了預設的程序,表現為跨域作戰單元在統一規則和共同任務下進行自組織、自適應的同步與協作。其本質是系統智能在作戰層面的體現。

規則約束下的時空協調。時空協調是指在統一的時空參考框架內,為分散部署的作戰單元設定行動邊界和交互規則,確保其在物理域內的有序協作。在統一的作戰規則框架下,智慧作戰系統的每個單元透過智慧演算法自主計算其相對位置並預測其軌跡,實現不同平台的時域校準、空域融合和頻域嵌套。這確保了無衝突的路徑規劃、無幹擾的頻譜使用和無事故的火力運用。這種兼具有序性和靈活性的協同機制,在保持戰術靈活性的同時避免了相互幹擾,為複雜戰場環境下的作戰行動提供了時空參考。

任務驅動的邏輯協調。邏輯協調是指以作戰任務為底層邏輯,自主分解任務、分配資源、規劃行動,進而達成智慧化的組織與調度。智慧作戰系統基於任務分析、能力匹配和計畫生成演算法,自動將作戰目標分解為具體的行動序列,並智慧調度相應的作戰單位進行「命令下達」。每個智慧節點基於對整體任務的理解、即時態勢感知以及自身能力,透過多智能體協商機制自主制定行動計劃,並與相關單位動態協商協作以「接受命令」。這種以任務為導向的指揮方式極大地解放了上級指揮官,使系統在應對突發事件時具備敏捷性和靈活性,顯著提升了任務適應性。

目標對齊感知協同。感知協同是指作戰單位基於對目標和環境的共同理解進行自主決策和行動,從而產生協同效應。智慧作戰系統由具備預測和推理能力的系統或節點組成。在營運目標的驅動下,它們可以智慧作戰系統能夠預判友軍行動和戰場局勢,透過局部感知和獨立決策,進行自組織、自發的協同支援。這種以效率為導向的、無聲的共識超越了溝通限制和預設程序,使系統在面對強大對手時展現出卓越的適應性和創造力。

學習迭代的演化優勢

演化優勢是作戰系統保持競爭力和在戰場上掌握主動權的關鍵。智慧作戰系統依靠即時對抗數據來驅動整體優化,透過跨域經驗轉移加速能力擴散,並透過虛擬博弈環境培養顛覆性戰術,從而在對抗過程中實現自主演化和作戰效能的世代飛躍。

基於經驗累積的系統演化。智慧作戰系統將從複雜的對抗環境中即時獲得的感知、決策和行動數據收集到知識中心。利用強化學習等先進演算法,該系統將進行深度分析和挖掘,對系統級運作邏輯(如指揮流程、協調規則和資源分配策略)進行閉環評估和動態調整,從而形成可重用、可驗證的結構化知識單元,增強作戰系統對環境的理解和自主適應能力。這將使整個系統形成共享的“集體記憶”,實現從單點智慧到整體作戰效能的自適應輻射,並最終實現“越戰越精進”的個體演進。

跨域知識遷移賦能。智慧作戰系統依托統一的語意空間和特徵對齊框架,能夠將從特定戰場或領域提取和總結的局部經驗快速嵌入到其他作戰領域或任務場景中,打破作戰單元之間的資訊壁壘,實現作戰經驗的無損轉換和跨域應用。本質上,它促進了系統內知識的安全流動和協同效應,完成了從「具體經驗」到「抽象知識」的昇華和重構,實現了「一戰多域」的效益,並加速了跨領域作戰能力的同步演進。這不僅顯著提高了作戰系統的整體學習效率,避免了重複試錯,而且實現了作戰能力的強化和系統繼承。

博弈論與對抗的顛覆性潛能正在顯現。系統智慧博弈論旨在突破人類認知的限制,培養超越傳統經驗的顛覆性作戰能力。其本質在於系統層面知識的主動創造與自我超越。透過在數位孿生戰場上建構高強度、長期、逼真的「紅藍」對抗環境,並利用生成對抗網路和多智能體強化學習框架,智慧作戰系統能夠在持續的博弈演進中探索戰略空間的未知邊界。基於博弈論和複雜系統理論,該系統能夠在對抗演化過程中自發性地形成更優策略,從而產生超越傳統認知的作戰模式和組織形式。這使得該智慧作戰系統成為一個能夠持續產生顛覆性戰術的「超級智庫」。

中國原創軍事資源:https://military.people.com.cn/n18/2025/18216/c1011-480682584829.html

Where is the Transformation of Chinese Military Intelligent War Preparedness Heading?

中國軍事情報戰備轉型將走向何方?

現代英語:

Where should the intelligent transformation for combat readiness go?

Currently, the form of warfare is rapidly evolving towards intelligence, and the era of intelligent warfare is imminent. To adapt to the development of military intelligent technology, the changing mechanisms of war, and the high-quality development of the armed forces, it is imperative to accelerate the advancement of intelligent combat readiness. Modern combat readiness must, while advancing the transformation from mechanization and semi-mechanization to informatization, further proactively address the challenges of military intelligence, adhere to intelligence as the guiding principle, and accelerate the integrated development of mechanization, informatization, and intelligence. In short, vigorously promoting intelligent combat readiness is a practical necessity for driving the high-quality development of national defense and the armed forces; only by successfully transforming to intelligent combat readiness can we promote the leapfrog development of the military’s combat capabilities.

Construct an intelligent warfare theoretical system. Focusing on solving key and difficult issues in intelligent warfare theory, such as war prediction, war forms, war design, operational concepts, operational styles, operational systems, troop formation, and troop training, we will deepen research on the application of intelligent warfare, explore the winning mechanisms, characteristics, laws, tactics, action methods, and comprehensive support of intelligent warfare, enrich the theories of intelligent warfare, intelligent operations, and the construction of intelligent combat forces, and gradually construct an intelligent warfare theoretical system.

Establish an intelligent command and control paradigm. Strengthen the development of technologies such as adversarial and game-theoretic operational planning, digital twin parallel simulation, and efficient organization and precise scheduling of complex operational resources. Enhance capabilities such as automatic planning of operational plans under large-scale, high-intensity conditions and autonomous decomposition of cross-domain and cross-level tasks. Achieve deep integration of military knowledge and machine intelligence, reliable and explainable auxiliary decision-making, and self-learning and self-evolving adversarial strategies. Integrate technological achievements such as sensing, networking, cloud computing, and quantum computing to enhance intelligent auxiliary capabilities in situation generation, operational command, and staff operations. Accelerate the development of intelligent staff business systems and intelligently upgrade and transform operational command information systems. Achieve intelligent information Q&A, intelligent plan generation, and decision support suggestions for typical campaign/tactical command, greatly reducing the workload of staff personnel and significantly improving the timeliness of command operations.

Develop intelligent weapon and equipment systems. Strengthen the intelligent upgrading and transformation of traditional weapons, promote the practical application of intelligent technologies in backbone equipment, and deploy low-cost, expendable unmanned combat platforms on a large scale. Develop intelligent individual soldier integrated systems, air-to-ground unmanned swarm collaborative attack systems, and underground space swarm warfare systems, etc., research and develop intelligent flexible wearable technologies and mobile intelligent terminal technologies, develop intelligent wearable equipment, brain-computer interface helmets, and human implant devices, etc., and accelerate the application of intelligent new weapon platforms, using the pioneering development of key equipment to drive overall breakthroughs.

Increase the proportion of intelligent combat forces. Focusing on optimizing structure and function, implement intelligent design for the existing organizational structure of the armed forces, and gradually increase the proportion of intelligent combat forces. Formulate talent development plans, cultivate the intelligent literacy of combat personnel, and explore a talent cultivation path that integrates military and civilian sectors, services, and enterprises. Build a new generation of combat forces that are intelligently led, cross-domain collaborative, all-domain mobile, and precise and multi-functional; focus on research on intelligent air defense and anti-missile systems, passive detection and intelligent identification of aerial targets, and build intelligent air combat forces such as anti-aircraft unmanned combat aircraft and “swarm” aircraft; emphasize research on intelligent missiles and develop long-range missile deterrence and strike capabilities; deepen research on the architecture design of intelligent attack and defense systems in cyberspace and the intelligent generation of attack strategies, upgrade the new generation of cyberspace reconnaissance, attack, and defense forces, and comprehensively enhance intelligent combat capabilities.

Optimize intelligent autonomous collaboration methods. Focusing on the human-machine “interaction-understanding-co-progress” framework, break through human-machine hybrid perception enhancement and human-machine adaptive multi-task collaboration to improve human-machine hybrid perception capabilities, cognitive abilities, and overall combat effectiveness in complex battlefield environments, achieving complementarity and intelligent enhancement between human wisdom and machine intelligence. Accelerate the development of applied research in areas such as intelligent swarm distributed elastic architecture, self-organizing anti-jamming communication and interaction, distributed autonomous collaboration in complex confrontation scenarios, and swarm intelligent command and control adapted to complex environments and tasks. Enhance the autonomous elastic planning and swarm intelligence confrontation learning capabilities of unmanned swarms in complex scenarios, promoting an overall leap in the combat effectiveness of multi-domain/cross-domain heterogeneous swarms.

Innovate an intelligent, all-dimensional support model. Facing the overall requirements of comprehensive support for future battlefields, including all-time intelligent perception, precise control of supplies and ammunition, and accurate delivery of combat supplies, enhance the intelligent combat logistics equipment support capabilities. Develop capabilities such as comprehensive multi-dimensional support demand mining across all domains, online networked dynamic monitoring of equipment status, autonomous early warning of support risks, and on-demand allocation of support resources. Promote research and verification of intelligent network information systems, intelligent military logistics systems, intelligent support for battlefield facilities and environment information, smart individual soldier support, intelligent rapid medical treatment for future battlefields, and intelligent energy support and transportation delivery, achieving the organic integration of combat, technology, and logistics support elements with combat command and troop movements.

現代國語:

智慧戰備轉型應走向何方?

當前,戰爭形式正迅速朝向智慧化演進,智慧戰時代迫在眉睫。為適應軍事智慧技術的發展、戰爭機制的轉變以及軍隊高品質發展,加速推動智慧戰備勢在必行。現代戰備在推動從機械化、半機械化轉型為資訊化的同時,必須更積極主動地應對軍事情報挑戰,堅持以情報為指導原則,加速機械化、資訊化、情報化整合發展。總之,大力推動智慧戰備是推動國防和軍隊高品質發展的現實需求;只有成功實現智慧戰備轉型,才能推動軍隊作戰能力的跨越式發展。

建構智能戰理論體系。我們將著力解決智慧戰理論中的關鍵難點問題,例如戰爭預測、戰爭形態、戰爭設計、作戰理念、作戰風格、作戰體系、部隊編組和部隊訓練等,深化智能戰應用研究,探索智能戰的製勝機制、特徵、規律、戰術、行動方法和綜合保障,豐富智能戰、智能作戰和智能作戰力量建設的理論,逐步構建的理論體系。

建立智慧指揮控制範式。加強對抗性與博弈論作戰規劃、數位孿生並行模擬、複雜作戰資源高效組織和精確調度等技術的研發。提升大規模、高強度條件下作戰計畫的自動規劃、跨域、跨層級任務的自主分解等能力。實現軍事知識與機器智慧的深度融合,實現可靠、可解釋的輔助決策,以及對抗策略的自學習、自我演化。整合感知、網路、雲端運算、量子運算等技術成果,提升態勢生成、作戰指揮、參謀運作等方面的智慧輔助能力。加速智慧參謀業務系統建設,實現作戰指揮資訊系統的智慧升級改造。實現典型戰役/戰術指揮的智慧資訊問答、智慧計畫生成、決策支援建議,大幅減輕參謀人員工作負擔,顯著提升指揮運作的時效性。

發展智慧武器裝備系統。加強傳統武器的智慧升級改造,推動智慧技術在骨幹裝備的實際應用,大規模部署低成本、消耗型無人作戰平台。研發智慧單兵一體化系統、空地無人群聚協同攻擊系統、地下空間集群作戰系統等,研發智慧柔性穿戴技術與行動智慧終端技術,開發智慧穿戴設備、腦機介面頭盔、人體植入式設備等,加速智慧新型武器平台的應用,以關鍵裝備的先導研發為驅動力,實現整體突破。

提高智慧作戰力量比例。著力優化結構與功能,對現有軍隊組織結構進行智慧化設計,逐步提升智慧作戰力量比例。制定人才培育計劃,提升作戰人員的智慧素養,探索軍民融合、服務業與企業融合的人才培育路徑。建構智慧主導、跨域協同、全域機動、精準多功能的新一代作戰力量;重點研發智慧防空反導系統、空中目標被動偵測與智慧辨識技術,建構以防空無人作戰飛機、「群聚」飛機等為代表的智慧空戰力量;重視智慧飛彈研發,發展遠程飛彈威懾與打擊能力;深化網路空間太空防空防電系統設計與智慧飛彈威懾策略的新一代攻擊能力。全面提升網路空間偵察、攻擊和防禦力量的智慧作戰能力。

優化智慧自主協同作戰方式。圍繞人機「互動-理解-協同-進步」框架,突破人機混合感知增強和人機自適應多任務協同作戰,提升複雜戰場環境下人機混合感知能力、認知能力和整體作戰效能,實現人機智慧互補與智能增強。加速智慧集群分散式彈性架構、自組織抗干擾通訊與互動、複雜對抗場景下的分散式自主協同作戰、適應複雜環境和任務的集群智慧指揮控制等領域的應用研究。增強複雜場景下無人群集的自主彈性規劃與群集智慧對抗學習能力,推動多域/跨域異質群集作戰效能的全面飛躍。

創新智能化全維度支援模式。面對未來戰場全面保障的整體需求,包括全時智慧感知、物資彈藥精準管控、作戰物資準確投放等,提升智慧作戰後勤裝備保障能力。發展跨域多維綜合保障需求挖掘、裝備狀態線上網路動態監控、保障風險自主預警、保障資源按需調配等能力。推動智慧網路資訊系統、智慧軍事後勤系統、戰場設施及環境資訊智慧保障、智慧單兵保障、未來戰場智慧快速醫療救治、智慧能源保障及運輸配送等研究驗證,實現作戰、技術、後勤支援要素與作戰指揮、部隊調動有機融合。

陶利民,秦昊

來源:中國軍網-解放軍報 作者:陶立民 秦浩 責任編輯:王粲

中國原創軍事資源:http://www.81.cn/ll_20888543/186482825186.html

STRENGTHENING THE FOUNDATION FOR CHINESE MILITARY INTELLIGENT TRANSFORMATION

加強中國軍事情報轉型的基礎

現代英語:

The nature of warfare is rapidly evolving towards intelligence. The intelligent transformation of the military is not merely a simple accumulation of technologies, but a systemic change supported by data, algorithms, and computing power. These three elements mutually empower and organically integrate, forming the technological foundation for generating new combat capabilities. To accelerate the intelligent development of the military, we must deeply grasp the technological logic of intelligent transformation, solidify the data foundation, activate the algorithm engine, and strengthen computing power support to provide a solid guarantee for winning future intelligent wars.

Operational data: the “digital cornerstone” of intelligent transformation

Data is the “lifeblood” of intelligence. Without the accumulation of high-quality, large-scale, and multi-dimensional operational data, the transformation of military intelligence will be like water without a source or a tree without roots. In intelligent warfare, all activities across the entire chain, including battlefield perception, command and decision-making, and combat operations, are essentially processes of data generation, flow, processing, and application. The completeness, accuracy, and timeliness of operational data directly determine the perception precision, decision-making speed, and strike accuracy of intelligent systems, and are an indispensable cornerstone for the intelligent transformation of the military field.

The core value of operational data lies in breaking through the “fog of war” and enabling a shift from experience-driven to data-driven approaches. In traditional warfare, commanders primarily rely on battlefield reconnaissance, intelligence analysis, and combat experience to make decisions. Limited by the breadth and depth of information acquisition, these decisions often carry a degree of subjectivity and limitation. However, in the era of intelligent warfare, a single reconnaissance drone can transmit 5GB of image data per second, and satellite networks constantly track tens of thousands of ground targets, resulting in a geometrical increase in the rate of battlefield data generation. This operational data, originating from multiple domains including land, sea, air, space, cyber, electronic, and psychological domains, can, after standardized processing and in-depth analysis, construct a transparent battlefield situation across all domains, providing commanders with precise decision-making support.

Building a comprehensive operational data resource system requires focusing on key aspects of the entire lifecycle governance. In the data acquisition phase, it’s essential to base data acquisition on the needs of all-domain operations, broaden data source channels, and achieve full coverage of data in both traditional and new domains. Traditional domains should focus on land, sea, and air battlefields, accurately collecting data on troop deployments, equipment performance, and terrain. New domains should extend to outer space, deep sea, polar regions, and cyberspace, prioritizing the collection of data on space target trajectories, deep-sea environmental parameters, and cyberspace situational awareness. In the data fusion and processing phase, a unified data standard system must be established to address prominent issues such as multiple values ​​for a single data point and inconsistent formats, achieving interconnectivity between data from different sources and of different types. In the data sharing phase, a sound cross-domain sharing mechanism must be established, along with tiered and categorized sharing rules, breaking down service-specific barriers, departmental boundaries, and network isolation to build a ubiquitous, all-encompassing, and interconnected data sharing environment, maximizing the utilization of data resources.

To fully leverage the multiplier effect of combat data, the key lies in cultivating data-driven thinking and building a strong professional team. Data-driven thinking is the prerequisite for activating data value. It is essential to guide officers and soldiers to develop the habit of “thinking with data, speaking with data, managing with data, and making decisions with data,” abandoning traditional thinking patterns based on experience and intuition. In operational planning, quantitative analysis should be based on data; in training evaluation, precise measurement should be based on data standards; and in equipment development, iterative optimization should be supported by data. Simultaneously, efforts should be focused on building a professional data talent team, clarifying the responsibilities of each position, and connecting the entire process from data generation to data application. Through various means such as academic training, on-the-job experience, and specialized training, the professional skills of officers and soldiers in data collection, processing, analysis, and application should be improved, creating a composite talent team that understands both military operations and data technology, providing talent support for releasing the value of data.

Specialized Algorithms: The “Digital Engine” of Intelligent Transformation

If data is the “fuel” of intelligence, then algorithms are the “engine” that transforms fuel into power. Specialized algorithms, as the core driving force of military intelligence, are the key link in realizing the transformation of data into knowledge, knowledge into decision-making, and decision-making into combat effectiveness. In intelligent warfare, the quality of algorithms directly determines the reaction speed, decision-making accuracy, and combat effectiveness of the combat system, becoming the engine of intelligent transformation in the military field.

The core advantage of algorithms lies in reconstructing the operational chain and achieving rapid iteration of the OODA loop. In traditional warfare, the chain of observation, judgment, decision-making, and action is lengthy and often struggles to adapt to rapidly changing battlefield situations due to limitations in human processing capabilities. Intelligent algorithms, however, can leverage machine learning, deep learning, and other technologies to process massive amounts of operational data in seconds, perform real-time analysis, and uncover patterns, significantly shortening the decision-making cycle. In simulation tests, foreign military AI command systems generated multiple complete operational plans in a very short time, demonstrating response speed and decision-making efficiency far exceeding that of human command teams, fully showcasing the enormous advantages of algorithms in accelerating the decision-making process. In combat operations, algorithms can span the entire chain, from reconnaissance and perception, command and decision-making, fire strikes, and effect assessment, constructing an autonomous, closed-loop “kill chain.” From target identification to threat ranking, from plan generation to fire allocation, from strike implementation to damage assessment, algorithms can autonomously complete a series of complex tasks, achieving a “detect and destroy” operational effect.

Enhancing the practical application effectiveness of algorithms requires strengthening technological innovation and scenario empowerment. In terms of technological innovation, it is essential to keep pace with the development trends of artificial intelligence and accelerate the military application transformation of cutting-edge algorithms. Focusing on emerging technologies such as generative AI, neuromorphic computing, and brain-computer interfaces, we should explore pathways for the deep integration of algorithms with military needs. Regarding scenario empowerment, we must build diverse typical scenarios for algorithms based on actual combat requirements, develop specialized algorithms for target recognition, situational assessment, and virtual training, overcome bottlenecks in information processing in complex electromagnetic environments, promote the modularization and lightweight transformation of algorithms, and rapidly integrate them with command and control systems and unmanned equipment systems. This will allow algorithms to continuously iterate and optimize in specific tasks within typical scenarios, transforming algorithmic advantages into practical combat capabilities.

Strengthening algorithm security is crucial for ensuring the steady and sustainable development of intelligent transformation. While algorithms enhance combat effectiveness, they also face security risks such as tampering, deception, and misuse, potentially leading to serious consequences like “algorithmic runaway.” It is essential to establish an algorithm security review mechanism to conduct full-process security assessments of algorithm models in military intelligent systems, focusing on their reliability, transparency, and controllability to prevent algorithmic bias and logical vulnerabilities. Strengthening the research and development of algorithmic countermeasures technologies is also vital. This involves improving the anti-interference and anti-attack capabilities of our own algorithms while mastering techniques to interfere with and deceive enemy algorithms, thus gaining the initiative in algorithmic confrontation. Simultaneously, it is crucial to emphasize algorithmic ethics, clearly defining the boundaries and rules of algorithm application to ensure that algorithm development and use comply with international laws and ethical standards, avoiding any violations of war ethics.

Supercomputing Power: The “Digital Energy” for Intelligent Transformation

Computing power is the fundamental capability supporting data processing and algorithm execution, much like the “energy support” for intelligent systems. In the transformation towards military intelligence, the explosive growth of data and the increasing complexity of algorithms have placed unprecedented demands on computing power. The scale, speed, and reliability of supercomputing power directly determine the operational efficiency and combat effectiveness of military intelligent systems, becoming the driving force behind the intelligent transformation of the military field.

The core role of computing power lies in overcoming performance bottlenecks and supporting the efficient operation of complex intelligent tasks. The demand for computing power in intelligent warfare exhibits an “exponential growth” characteristic: an advanced AI command system needs to run thousands of algorithm models simultaneously when processing battlefield data across the entire domain; a swarm of drones performing collaborative combat missions requires real-time interaction and decision-making calculations involving massive amounts of data; a large-scale virtual combat training exercise needs to simulate the interactive behaviors of tens or even hundreds of thousands of combat units. The completion of these complex tasks is inseparable from powerful computing power. Without sufficient computing power, even the highest quality data cannot be processed quickly, and even the most advanced algorithms cannot operate effectively. Currently, computing power has become a crucial indicator for measuring the level of military intelligence; whoever possesses stronger computing power holds the initiative in intelligent warfare.

Building a computing power system adapted to the needs of intelligent transformation requires creating a collaborative computing power layout across the cloud, edge, and terminal. In the cloud, distributed cloud computing centers need to be constructed to build a computing power foundation that covers the entire domain and is elastically scalable. Relying on infrastructure such as big data centers and supercomputing centers, various computing resources should be integrated to form a large-scale, intensive computing power supply capability. At the edge, computing power should be deployed more readily, enhancing the autonomous computing capabilities of the battlefield. For special scenarios such as forward positions, naval vessels, and air platforms, miniaturized, low-power, and highly reliable edge computing nodes should be developed to transfer some computing tasks from the cloud to the edge. This reduces reliance on communication links and data transmission latency, and ensures that combat units can autonomously complete basic tasks such as target identification, path planning, and coordination even in extreme environments such as communication interruptions or signal blackouts, thus improving the system’s survivability. At the terminal, the built-in computing power of equipment should be strengthened to improve the intelligence level of individual combat platforms. By embedding high-performance AI chips into platforms such as drones, unmanned vehicles, and missile weapons, equipment is endowed with the ability to autonomously perceive, make decisions, and act, making it an intelligent unit with independent combat capabilities and laying the foundation for cluster collaboration and system-on-system confrontation.

Enhancing the combat readiness of computing power support requires strengthening technological innovation and security protection. In terms of technological innovation, it is crucial to keep pace with the development trends of computing power technology and accelerate the military application of new computing technologies. Focusing on cutting-edge areas such as quantum computing, photonic computing, and neuromorphic computing, we must break through the performance bottlenecks of traditional computing architectures and develop disruptive new computing power equipment. Simultaneously, we must strengthen the construction of computing power networks, building high-bandwidth, low-latency, and interference-resistant computing power transmission networks. By integrating technologies such as 5G, 6G, and satellite communication, we can ensure computing power collaboration and data interaction between the cloud, edge, and terminals, achieving seamless connection and efficient scheduling of computing power resources. In terms of security protection, we must establish a computing power security system to prevent the risks of attacks, hijacking, and misuse of computing power resources. By adopting technologies such as encrypted computing and trusted computing, we can ensure the security and privacy of data during the computing process; strengthen the physical and network protection of computing power facilities, and build a multi-layered, all-round protective barrier to ensure that the computing power system can operate stably in wartime and is not subject to enemy interference or damage.

現代國語:

戰爭形態正加速向智慧化演進,軍事領域的智慧轉型絕非單純的技術疊加,而是以數據、演算法、算力為核心支撐的體系性變革,三者相互賦能、有機融合,構成了新型戰鬥力生成的技術基礎。加速軍事領域智慧化發展進程,應深刻掌握智慧轉型的技術邏輯,夯實數據基石、啟動演算法引擎、做強力支撐,為打贏未來智慧化戰爭提供堅實保障。

作戰數據:智慧轉型的“數位基石”

數據是智慧化的“血液”,沒有高品質、大規模、多維度的作戰數據積累,軍事智慧轉型就會成為無源之水、無本之木。在智慧化戰爭中,戰場感知、指揮決策、作戰行動等全連結活動,本質上都是資料的產生、流轉、處理與應用過程。作戰數據的完備性、準確性和時效性,直接決定了智慧系統的感知精度、決策速度和打擊準度,是軍事領域智慧轉型不可或缺的基石。

作戰資料的核心價值在於打破“戰爭迷霧”,實現從經驗驅動到數據驅動的轉變。在傳統戰爭中,指揮官主要依賴戰場偵察、情報研判和實戰經驗來做出決策,受限於資訊獲取的廣度和深度,決策往往帶有一定的主觀性和限制。而在智慧化戰爭時代,一架偵察無人機每秒可傳回5GB影像數據,衛星網路時刻追蹤成千上萬個地面目標,戰場數據生成速率呈幾何級數增長。這些來自陸、海、空、天、網、電、心理等多域的作戰數據,經過規範化處理和深度挖掘後,能夠建構起全局透明的戰場態勢,為指揮官提供精準決策支撐。

建構全域覆蓋的作戰資料資源體系,需要抓好全生命週期治理的關鍵環節。在資料擷取環節,要立足全域作戰需求,拓寬資料來源管道,實現傳統空間與新域空間的資料全覆蓋。傳統空間要聚焦陸戰場、海戰場、空戰場等傳統領域,精準採集兵力部署、裝備性能、地形地形等資料;新域空間要向太空、深海、極地、網路空間等領域延伸,重點收集太空目標軌跡、深海環境參數、網路空間態勢等資料。在資料融合處理環節,要建立統一的資料標準體系,解決「一數多值」「格式不一」等突出問題,實現不同來源、不同類型資料的互聯互通。在資料共享環節,要健全跨域共享機制,建立分級分類共享規則,打破軍種壁壘、部門界限和網路隔離,建構「無所不在、無所不含、無所不聯」的數據共享環境,實現數據資源的最大化利用。

發揮作戰數據的戰鬥力倍增效應,關鍵在於培育數據思維與建強專業隊伍。數據思維是啟動數據價值的前提,要引導官兵養成「用數據思考、用數據說話、用數據管理、用數據決策」的行為習慣,摒棄憑經驗、靠直覺的傳統思維模式。在作戰籌劃中,要以數據為依據進行量化分析;在訓練評估中,要以數據為標準進行精準衡量;在裝備研發中,要以數據為支撐進行迭代優化。同時,要著力建構專業化的資料人才隊伍,明確各環節職務職責,貫通從資料產生到資料運用的全流程連結。透過院校培養、職缺歷練、專案訓練等多種方式,提升官兵資料收集、處理、分析、運用的專業技能,打造一支既懂軍事業務又通資料技術的複合型人才隊伍,為資料價值釋放提供人才支撐。

專業演算法:智慧轉型的“數位引擎”

如果說數據是智慧化的“燃料”,那麼演算法就是將燃料轉化為動力的“引擎”。專業演算法作為軍事智慧的核心驅動力,是實現數據向知識、知識向決策、決策轉化為戰鬥力的關鍵環節。在智慧化戰爭中,演算法的優劣直接決定了作戰體系的反應速度、決策精準度和對抗效能,成為軍事領域智慧轉型的引擎。

演算法的核心優勢在於重構作戰鏈路,實現OODA循環的極速迭代。傳統作戰中,觀察、判斷、決策、行動的連結較長,受限於人工處理能力,往往難以適應瞬息萬變的戰場態勢。而智慧演算法能夠依賴機器學習、深度學習等技術,對海量作戰資料進行秒級處理、即時分析與規律挖掘,大幅縮短決策週期。外軍AI軍事指揮系統在模擬測試中,僅用很短時間就生成多套完整作戰方案,響應速度和決策效率遠超人類指揮團隊,充分展現了演算法在加速決策流程中的巨大優勢。在作戰行動中,演算法能夠貫穿偵察感知、指揮決策、火力打擊、效果評估等全鏈路,建構自主閉環的「殺傷鏈」。從目標識別到威脅排序,從方案生成到火力分配,從打擊實施到毀傷評估,演算法能夠自主完成一系列複雜任務,實現「發現即摧毀」的作戰效果。

提升演算法的實戰應用效能,需要強化技術創新與場景賦能。在技​​術創新方面,要緊跟人工智慧發展趨勢,加速前沿演算法的軍事應用轉換。聚焦生成式AI、神經形態運算、腦機介面等新技術方向,探索演算法與軍事需求的深度融合路徑。在場景賦能方面,要立足實戰需求建構多元演算法典型場景,研發目標辨識、態勢研判、虛擬訓練等專用演算法,突破複雜電磁環境資訊處理瓶頸,推動演算法模組化、輕量化改造,與指揮控制系統、無人裝備系統快速整合,讓演算法在典型場景具體任務中不斷迭代優化,讓優勢轉化為最佳化演算法。

築牢演算法安全防線,是確保智慧轉型行穩致遠的重要保障。演算法在帶來作戰效能提升的同時,也面臨被竄改、被欺騙、被濫用等安全風險,甚至可能出現「演算法失控」的嚴重後果。要建立演算法安全審查機制,對軍事智慧系統中的演算法模型進行全流程安全評估,重點在於審查演算法的可靠性、透明度和可控性,防止演算法偏見、邏輯漏洞等問題。加強演算法對抗技術研發,既要提升己方演算法的抗干擾、抗攻擊能力,也要掌握幹擾、欺騙敵方演算法的技術手段,在演算法對抗中佔據主動。同時,要注重演算法倫理建設,明確演算法應用的邊界和規則,確保演算法的研發和使用符合國際法律和倫理標準,避免違反戰爭倫理的情況。

超智算力:智慧轉型的“數位能量”

算力是支撐資料處理和演算法運作的基礎能力,如同智慧化體系的「能量支撐」。在軍事智慧轉型中,數據的爆炸性成長和演算法的複雜化發展,對算力提出了前所未有的高要求。超智算力的規模、速度和可靠性,直接決定了軍事智慧系統的運作效率和實戰效能,成為軍事領域智慧轉型的動力系統。

算力的核心作用在於突破性能瓶頸,支撐複雜智慧任務的高效運作。智慧化戰爭對算力的需求呈現出「指數級增長」特徵:一套先進的AI指揮系統,在處理全局戰場數據時,需要同時運行數千個演算法模型;一支無人機蜂群在執行協同作戰任務時,需要實時進行海量數據交互和決策計算;一次大規模的虛擬對抗訓練,需要模擬數萬甚至數十萬作戰單元的互動行為。這些複雜任務的完成,離不開強大的算力支撐。沒有足夠的算力,再優質的數據也無法快速處理,再先進的演算法也無法有效運作。目前,算力已成為衡量軍事智慧化程度的重要指標,誰掌握了更強的算力,誰就掌握了智慧對抗的主動權。

建構適應智慧轉型需求的算力體系,需要打造「雲端端」協同的算力佈局。在雲端,要建置分散式雲算力中心,建構覆蓋全域、彈性伸縮的算力基座。依託大資料中心、超級運算中心等基礎設施,整合各類運算資源,形成規模化、集約化的算力供給能力。在邊端,要推進算力下沉部署,提升戰場末端的自主運算能力。針對前線陣地、海上艦艇、空中平台等特殊場景,研發小型化、低功耗、高可靠的邊緣運算節點,將部分運算任務從雲端轉移至邊緣端。這樣既可以降低對通訊鏈路的依賴,減少資料傳輸延遲,又能在通訊中斷或訊號黑障等極端環境下,保障作戰單元自主完成目標辨識、路徑規劃、協同配合等基本任務,提升體系生存能力。在終端,要強化裝備內置算力,提升單一作戰平台的智慧等級。透過在無人機、無人車、飛彈武器等平台中嵌入高性能AI晶片,賦予裝備自主感知、自主決策、自主行動的能力,使其成為具備獨立作戰能力的智慧單元,為集群協同和體系對抗奠定基礎。

提升算力保障的實戰化水平,需要強化技術創新與安全防護。在技​​術創新方面,要緊跟算力技術發展趨勢,加速新型計算技術的軍事應用。聚焦量子運算、光子運算、神經形態運算等前沿方向,突破傳統運算架構的效能瓶頸,研發具有顛覆性的新型算力裝備。同時,要加強算力網路建設,建構高頻寬、低時延、抗干擾的算力傳輸網路。透過融合5G、6G、衛星通訊等技術,確保雲端、邊端、終端之間的算力協同與資料交互,實現算力資源的無縫銜接與高效調度。在安全防護方面,要建立算力安全保障體系,防範算力資源被攻擊、被劫持、被濫用的風險。透過採用加密運算、可信任運算等技術,確保資料在運算過程中的安全性和隱私性;加強算力設施的實體防護和網路防護,建構多層次、全方位的防護屏障,確保算力系統在戰時能夠穩定運行,不受敵方幹擾破壞。 (李建平、紀鳳珠、趙輓)

2025年12月30日09 | 資料來源:解放軍報

中國原創軍事資源:https://military.people.com.cn/n1/2025/1230/c1011-40688835461.html

A Look at Chinese Intelligent Warfare | “Order Dispatch”: A New Style of Precision Strike

中國情報戰概覽 | 「命令派遣」:一種新型的精確打擊方式

現代英語:

“Order Dispatch”: Precise Targeting of New Patterns

  introduction

  As Lenin said, “Without understanding the times, one cannot understand war.” In recent years, the widespread application of information and intelligent technologies in the military field has promoted the deep integration of technology and tactics. Relying on intelligent network information systems, it has given rise to “order-based” precision strikes. Commanders and command organs can generate strike requirements in a formatted manner according to combat missions. The decision-making system intelligently matches strike platforms, autonomously plans action paths, and scientifically selects strike methods based on personalized requirements such as strike time, operational space, and damage indicators, thereby rapidly and accurately releasing strike effectiveness.

  The operational characteristics of “order dispatch” type precision strike

  As the informatization and intelligence of weapons and ammunition continue to improve, the cost of modern warfare is also constantly increasing. How to achieve the highest cost-effectiveness ratio with limited strike resources and maximize combat effectiveness has become a central issue for commanders and command organs in operational planning. “Order-based” precision strikes can provide a “feasible solution” for this.

  Real-time, precise, and targeted strikes. Modern warfare places greater emphasis on structurally disrupting enemy operational systems, achieving operational objectives through the rapid and precise release of combat effectiveness. This requires commanders and command organs to seize fleeting “windows of opportunity” to strike high-value, nodal, and critical targets within an enemy’s operational system before the enemy can react. The traditional “detection-guided-strike-assessment” operational loop is time-consuming and ineffective. Therefore, “order-based” precision strikes rely on advanced intelligent network information systems, without pre-determining strike platforms. Target lists are released in real-time, and auxiliary decision-making systems rapidly assess the strike performance of various weapon platforms and the expected damage to targets. Tasks are autonomously allocated to strike platforms, rapidly linking and controlling multi-domain firepower, autonomously closing the kill chain, and conducting rapid strikes against key targets.

  Multi-domain coordinated strike. The advantage of modern precision strike over traditional firepower lies in its information-based and intelligent combat system. It requires no human intervention and autonomously completes tasks such as reconnaissance, control, strike, and assessment based on a closed strike chain. This not only saves strike costs and reduces resource waste but also enables adaptive coordination based on unified operational standards. Therefore, “order-based” precision strikes require firepower forces distributed across various operational domains to establish a unified standard grid. Once a demand is issued from one point, multiple points can respond and coordinate globally, flexibly concentrating forces and firepower, using multiple means to rapidly and multi-domain convergence, and determining the strike direction, sequence, and method for each strike platform while on the move. Through system integration, time is effectively saved, enabling multi-domain precision strikes against key enemy nodes and critical parts of core targets, fully leveraging the combined power of the integrated combat effectiveness of various operational units.

  The key to victory lies in swift and decisive action. Modern warfare is a “hybrid war” conducted simultaneously across multiple domains, where the interplay and confrontation of new domains and new types of forces, such as information, aerospace, and artificial intelligence, are becoming increasingly pronounced. This necessitates that both sides be able to detect and act faster than the enemy, crippling their operational systems and reducing their operational efficiency. On the one hand, it is crucial to pinpoint key nodes in the enemy’s system and launch timely and precise strikes; on the other hand, it is essential to conceal one’s own intentions and strike forces, striking swiftly and unexpectedly. “Order-based” precision strikes perfectly meet these two requirements. Supported by network information systems, they intelligently integrate firepower from various domains, achieving multi-source information perception, data interconnection, and multi-domain coordinated strikes. This enables seamless and high-speed operation of “target perception—decision and command—firepower strike—damage assessment,” resulting in a high degree of information and firepower integration and the rapid achievement of operational objectives.

  The system of “order dispatch” type precision strike

  ”Order dispatch” precision strikes compress action time and improve strike effectiveness by building an efficient closed strike chain, enabling various fire strike platforms to better integrate into the joint fire strike system and provide rapid and accurate battlefield fire support. Its key lies in the “network” and its focus is on the “four” systems.

  Multi-domain platform access network. Supported by information and intelligent technologies, an integrated information network system with satellite communication as the backbone is established. Firepower strike platforms distributed across multiple domain battlefields are integrated into the combat network to create a battlefield “cloud.” Different combat modules are distinguished, and “sub-network clouds” such as “reconnaissance, control, strike, and assessment” are established. Relying on an integrated communication network, the “sub-network clouds” are linked to the “cloud.” This can enhance the firepower strike platform’s capabilities in all domains, all times, on the move, autonomous networking, and spectrum planning, and realize network interconnection between firepower platforms, domain combat systems, and joint combat systems, as well as the interconnection and interoperability of internal strike forces.

  Joint reconnaissance and sensing system. This system leverages various reconnaissance and surveillance forces within the joint operations system to achieve all-weather, multi-directional, and high-precision battlefield awareness of the operational area. This requires constructing a ubiquitous, multi-dimensional reconnaissance and sensing force system encompassing physical and logical spaces, tangible and intangible spaces. It involves widely deploying intelligent sensing devices to form an intelligence data “cloud.” Through this intelligence data “cloud,” the system analyzes the enemy situation, identifies key points in the enemy’s operational system and time-sensitive targets, updates reconnaissance information in real time, and displays target dynamics.

  Intelligent Command and Decision-Making System. Relying on a new command and control system with certain intelligent control capabilities, this system constructs various planning and analysis models, expands functions such as intelligent intelligence processing, intelligent mission planning, automatic command generation, and precise action control, and expands and improves databases such as target feature database, decision-making knowledge base, and action plan database. It strengthens the system support capabilities for mission planning, action decision-making, and control during combat organization and implementation, enhances planning and decision-making and combat action control capabilities, clarifies “how to fight, where to fight, and who will fight,” and achieves precise “order dispatch.”

  Distributed fire strike system. Relying on intelligent network information systems, on the one hand, it integrates multi-dimensional fire strike platforms across land, sea, air, and space, enhancing functions such as intelligent target identification and remote-controlled strike, enabling various combat modes such as remote-controlled operations, manned-unmanned collaborative operations, and flexible mobile operations; on the other hand, it can construct a low-cost fire strike platform mainly composed of low-altitude and ultra-low-altitude unmanned strike platforms such as racing drones and loitering munitions. By adding different functional combat payloads, it can closely coordinate with high-end fire strike platforms to carry out tasks such as battlefield guidance, precision strikes, and fire assessment, efficiently completing “orders”.

  Autonomous Damage Assessment System. This system, built upon reconnaissance and surveillance capabilities within the joint operations system, autonomously assesses the effectiveness of attacks on targets after the firepower platform has completed its strike. It conducts real-time, dynamic, objective, and systematic analysis and evaluation of the target’s external condition and degree of functional loss, and promptly transmits relevant information back to decision-making and command centers at all levels via video images. The assessment centers then determine “how well it went” and whether the expected damage requirements were met. If not, operational actions can be adjusted in a timely manner for supplementary strikes, providing strong support for maximizing operational effectiveness.

  The planning and implementation of “order dispatch” style precision strikes

  The “order dispatch” style of precision strike is similar to the operation of ride-hailing services. Through a series of processes such as formatted “order” generation, intelligent target matching, and autonomous route planning, it autonomously completes the “OODA” combat cycle, making its actions more efficient, its strikes more precise, and its collaboration closer.

  Real-time reporting of firepower requirements allows combat units to submit orders on demand. Reconnaissance elements distributed across different operational areas and multi-dimensional battlefield spaces are acquired through radar, optical, infrared, and technical reconnaissance methods, forming battlefield target intelligence information across a wide area and multiple sources. This information is transmitted to the battlefield information network via intelligence links, and is constantly relayed to combat units. Combat units then perform correlation processing, multi-source comparison and verification, and comprehensively compile battlefield target information to generate precise mission orders. Combat units analyze target value and connect to the decision-making platform as needed, constructing a closed-loop strike chain based on these orders, and submitting mission orders in real time, achieving dynamic optimization and precise adaptation.

  The decision-making center intelligently “dispatches” fire support missions, differentiating them from actual fire strike missions. Through the battlefield information network and relying on an intelligent mission planning system, the center can automatically analyze the mission “order” information data submitted by combat units. Based on the nature, coordinates, movement status, and threat level of battlefield targets, it automatically generates mission requirements such as the type and quantity of ammunition needed for fire strike operations, the strike method, and damage indicators, forming a fire support mission “order.” By intelligently matching the optimal fire support platform and connecting link nodes as needed, the center conducts intelligent command-based “order dispatch,” delivering the orders instantly to the standby fire support platforms.

  Optimal target matching is performed continuously, and firepower platforms swiftly “accept orders.” Multiple firepower platforms distributed across the battlefield respond rapidly to these orders via the battlefield information network. The platforms autonomously establish links with combat units, mutually verifying their identities before directly establishing a guided strike chain. They coordinate firepower strikes, adjusting strike methods and firing parameters in a timely manner based on target damage and battlefield target dynamics before conducting further strikes until the assigned mission is completed. Firepower platforms consistently adhere to the principle of “strike-relocate-strike-relocate,” completing strike missions and rapidly relocating to new positions, maintaining a state of constant readiness and receiving orders online in real time. After the mission concludes, the guided strike chain between the firepower platform and the combat unit is automatically terminated.

  Multi-source damage information acquisition and real-time assessment by the evaluation center. Utilizing a comprehensive range of long-range, intelligent, and information-based reconnaissance methods, including satellite, radar, and drone reconnaissance, multi-domain, three-dimensional reconnaissance is conducted to acquire real-time target fire damage information, providing accurate assessments for precision fire strikes. A comprehensive assessment of damage effects is performed, quantitatively and qualitatively evaluating the strike results, distinguishing between physical, functional, and systemic damage states, and promptly feeding back to the decision-making center. Based on the damage assessment results, timely adjustment suggestions are made to modify fire strike plans, optimize operational actions, and achieve precise control of fire strikes. This facilitates commanders’ accurate control of the operational process and efficient command and control of fire strike effectiveness.

現代國語:

「訂單派單」:精確打擊新樣式

引言

列寧說過,「不理解時代,就不能理解戰爭」。近年來,資訊化智慧化技術在軍事領域的廣泛運用,促進了技術與戰術深度融合,依托智能化網路資訊體系,催生出「訂單派單」式精確打擊。指揮及指揮機關可依據作戰任務格式化產生打擊清單需求,決策系統依據打擊時間、作戰空間、毀傷指標等個人化需求智慧匹配打擊平台、自主規劃行動路徑、科學選擇打擊方式,進而快速精準釋放打擊效能。

「訂單派單」式精準打擊的作戰特點

隨著武器彈藥資訊化智慧化程度不斷提升,現代作戰成本也不斷提高。如何運用有限打擊資源打出最高效費比,實現作戰效能最大化,已成為指揮員及指揮機關作戰籌劃的中心問題,「訂單派單」式精準打擊可為此提供「可行解」。

即時聚優精確釋能。現代作戰更強調對敵作戰體系進行結構性打擊破壞,透過快速且精準地釋放作戰效能來實現作戰目的。這就要求指揮官及指揮機關能夠抓住稍縱即逝時機的“窗口”,在敵未做出反應之時對其作戰體系內高價值、節點性、關鍵性目標實施打擊。傳統的「發現—引導—打擊—評估」的作戰環路耗時長,作戰效果不佳。因此,「訂單派單」式精確打擊,需要依托先進的智慧化網路資訊體系,不預先確定打擊平台,即時發布打擊目標清單,由輔助決策系統對各種武器平台的打擊性能與目標打擊毀傷預期等進行快速評估,自主分配打擊平台任務,快速連結調控多領域火力打擊力量,自主閉合殺傷鏈,對關鍵目標實施快速打擊。

多域聚能協同打擊。現代作戰精準打擊較以往火力打擊的優勢在於資訊化智能化的作戰體系,不需人工介入,依托閉合打擊鏈自主完成「偵、控、打、評」等任務,不僅能夠節省打擊成本,減少資源浪費,還能夠實現基於統一作戰標準的自適應協同。因此,「訂單派單」式精確打擊,需要分佈在各作戰領域的火力打擊力量能夠建立統一標準網格,只要一點發出需求,就能夠多點響應、全局聯動,靈活集中兵力、火力,多手段、快速多域聚能,動中確定各打擊平台打擊方向、打擊次序以及打擊方式。透過體系整合有效節約時間,對敵關鍵節點目標以及核心目標的關鍵部位實施多域精確打擊,充分發揮各作戰單元作戰效能疊加融合的整體威力。

擊要破體速戰速決。現代作戰是在多領域同步實施的“混合戰爭”,資訊、空天、智慧等新域新質力量交織影響、對抗更加明顯。這就需要作戰雙方能夠快敵一秒發現、快敵一步行動,毀癱敵作戰體系、降低敵體系運作效率。一方面,要透過找準敵體系節點,即時聚優精準打擊;另一方面,要隱藏己方企圖及打擊力量,乘敵不備快速打擊。 「訂單派單」式精確打擊能夠很好地契合這兩點需求,在網路資訊系統的支撐下,智慧融合各領域火力打擊力量,實現資訊多源感知、數據交鍊、多域協同打擊,實現「目標感知—決策指揮—火力打擊—毀傷評估」無縫高速運轉,資訊火力高度融合,快速達成作戰目的。

「訂單派單」式精確打擊的體系構成

“訂單派單”式精確打擊通過構建高效閉合打擊鏈,壓縮行動時間,提高打擊效果,使各火力打擊平台能夠更好地融入聯合火力打擊體系,並提供快速精準的戰場火力支援,其關鍵在“網”,重點在“四個”系統。

多領域平台接入網。在資訊化智慧化技術支撐下,建立以衛星通訊為骨幹的一體化資訊網系,將分佈在多維域戰場的火力打擊平台融入作戰網路建立戰場“雲”,區分不同作戰模組,建立“偵、控、打、評”等“子網雲”,並依託一體化的通訊網鏈將“子網雲”鏈入“雲端”,能夠提升火力打擊平台全局全時、動中接入、自主組網、頻譜規劃的能力,實現火力平台、分域作戰體系與聯合作戰體系的網絡互聯,以及內部打擊力量的互聯互通。

聯合偵察感知系統。依托聯合作戰體系內的各種偵察監視力量對作戰地域進行全天候、多方位、高精度戰場感知。這就要建構物理空間和邏輯空間、有形空間和無形空間泛在存在的全維域偵察感知力量系統,廣域佈設智能感知設備,形成情報數據“雲”,通過情報數據“雲”分析敵情態勢,找出敵作戰體系關鍵點以及時敏性目標,實時更新偵察信息,展現目標動態。

智能指揮決策系統。依托具備一定智能控制能力的新型指控系統,建構各類規劃分析模型,擴展情報智能處理、任務智能規劃、指令自動生成、行動精確控制等功能,擴充完善目標特徵庫、決策知識庫、行動預案庫等資料庫,強化戰鬥組織與實施過程中的任務規劃、行動決策和控制的系統支撐能力,提昇決定決策和戰鬥能力,明確怎麼打」。

分佈火力打擊系統。依托智慧網路資訊系統,一方面,融入陸、海、空、天等多維域火力打擊平台,強化目標智慧識別、遠程遙控打擊等功能,實現作戰單元遠程遙控作戰、有人無人協同作戰、靈活機動作戰等多種作戰方式;另一方面,可建構以穿越機、巡飛彈等低空超低空無人打擊平台為主的低成本火力打擊平台,透過加掛不同功能作戰載重,與高端火力打擊平台密切協同來實施戰場引導、精確打擊、火力評估等任務,高效完成「訂單」。

自主毀傷評估系統。依托聯合作戰體系內的偵察監視力量建構毀傷評估系統,在火力平台打擊完畢後,自主對目標實施打擊效果查核。主要就目標的外觀狀態、功能喪失程度等進行實時、動態、客觀、系統的分析和評估,並及時通過視頻圖像的方式將相關信息回傳至各級決策指揮中心,由評估中心判斷“打得怎麼樣”,是否達到預期毀傷要求。如不符合,可適時調控作戰行動,進行補充打擊,為最大限度釋放作戰效能提供強力支撐。

「訂單派單」式精確打擊的規劃實施

「訂單派單」式精準打擊就如同叫車的運作方式一樣,透過格式化「訂單」產生、智慧化物件配對、自主化路徑規劃等一系列流程,自主完成「OODA」作戰循環,其行動更為高效、打擊更為精準、協同更為密切。

即時提報火力需求,作戰單元按需「提單」。分佈在不同作戰地域、多維戰場空間的偵察要素,透過雷達、光學、紅外線和技術偵察等方式,廣域多源偵獲形成戰場目標情報資訊。這些資訊依托情報鏈路接入戰場資訊網,隨時隨地被傳至作戰單元,由作戰單元進行關聯處理、多方對比印證,綜合整編戰場目標訊息,產生精確的任務「訂單」。作戰單元分析目標價值按需連通決策平台,建構“訂單”式閉合打擊鏈,實時提報任務“訂單”,實現動中集優、精準適配。

區分火力打擊任務,決策中心智能「派單」。決策中心透過戰場資訊網,依托智能任務規劃系統,能夠自動解析作戰單元提報的任務「訂單」資訊數據,根據戰場目標性質、座標方位、移動狀態、威脅程度等,自動產生火力打擊行動所需彈種彈量、打擊方式和毀傷指標等任務要求,形成火力支援任務「訂單」,透過智慧服務火力平台,按需使用火力平台節點,按需通路,支援任務「訂單」。

全時匹配最優目標,火力平台迅即「接單」。多點分佈在戰場區域內的火力平台,透過戰場資訊網迅即響應“接單”,火力平台與作戰單元之間自主建鏈,相互核驗“身份”後直接建立引導打擊鏈,協同配合火力打擊行動,並根據打擊後目標毀傷情況以及戰場目標動態,及時調整打擊方式、射擊參數等,而後再次實施火力打擊,直至完成“派單”任務。火力平台始終遵循「打擊—轉移—打擊—轉移」的原則,完成打擊任務,迅即轉移陣地,全時保持待戰狀態,即時在線接收「訂單」。任務結束後,火力平台與作戰單元之間的引導打擊鏈會自動取消。

多源獲取毀傷訊息,評估中心即時「評單」。綜合運用衛星偵察、雷達偵察、無人機偵察等遠距離資訊化智慧化偵察手段,實施多域立體偵察,即時取得目標的火力毀傷訊息,為進行精確火力打擊提供準確評估。綜合判定毀傷效果,對打擊效果進行定量和定性評估,區分目標物理、功能和系統三種毀傷狀態,及時回饋至決策中心。根據打擊目標的毀傷評估結果,適時提出調控建議,調整火力打擊計劃,優化作戰行動,實現對火力打擊的精確控制,便於指揮員精準把控作戰進程,達成對火力打擊效能的高效指揮控制。 (高凱 陳良)

中國原創軍事資源:https://www.news.cn/milpro/20250123/8f71783cff6a4284a43871e996bc31888a7/c.html

Analysis of Chinese Military Development Trend of Collaborative Combat in the Era of Intelligentization

智能化時代中國協同作戰軍事發展趨勢分析

現代英語:

Operational coordination is a key element in modern warfare for achieving system-of-systems operations, unleashing overall effectiveness, and achieving operational objectives. In recent years, with breakthroughs in military science and technology, particularly artificial intelligence, the empowering and efficiency-enhancing role of technology has become increasingly prominent. While profoundly changing the nature of warfare and operational styles, it has also given rise to a new operational coordination model—autonomous coordination. Currently, we should scientifically grasp the opportunities and challenges of the new military revolution, dynamically coordinate the development of autonomous coordination, and thus accelerate the transformation and upgrading of operational methods.

Transforming towards intelligent empowerment and autonomous collaboration

Future warfare will be a comprehensive confrontation between opposing sides employing “human + intelligent equipment.” Limited by military technology, system platforms, and combat capabilities, traditional combat coordination, with its fixed cycles and low fault tolerance, is no longer suitable for the rapidly changing modern battlefield. With the powerful support of advanced technologies such as artificial intelligence and big data, the autonomy and automation of combat coordination will be greatly enhanced, and intelligently empowered autonomous coordination will become key to victory.

Wide-area ubiquitous collaboration. In recent years, the profound development of communication and intelligent technologies, along with the accumulation and superposition of data, algorithms, and computing power, has promoted the interconnection and aggregation of people, machines, things, and energy. This has extended the military Internet of Things (IoT) to many fields such as situational awareness, command and control, information and fire strikes, and logistical support. While promoting the iterative upgrading of combat capabilities, it has also provided more options for modern combat collaboration. It is foreseeable that the military IoT will shine on the future battlefield, serving not only as a key infrastructure supporting combat operations but also as a crucial hub for maintaining combat collaboration. Based on this, ubiquitous warfare characterized by wide-area dispersion of forces, modular organizational structures, and highly coordinated actions will emerge, characterized by being omnipresent, ubiquitous, and autonomous without control.

Deep human-machine collaboration. In the Nagorno-Karabakh conflict, the Azerbaijani army leveraged its drone advantage to build a strong battlefield advantage, marking the beginning of “robot warfare.” In future warfare, unmanned combat forces such as drones, unmanned vehicles, and unmanned ships are rapidly moving from back-end support to the front lines, becoming the “protagonists” of the battlefield. Compared to traditional combat collaboration, manned-unmanned intelligent collaboration exhibits characteristics such as decentralized command, de-division of labor in combat processes, advanced skill operation, and blurred lines between the front and rear, placing greater emphasis on human-machine collaboration and algorithmic victory. Especially in recent years, intelligent unmanned swarms have emerged as a powerful force, strongly impacting the modern battlefield. Faced with these new situations and changes, we should comprehensively utilize swarm formation algorithms, formation control algorithms, and complex scenario optimization algorithms to promote networked communication and intelligent collaboration between unmanned and manned systems, facilitating the integrated operation of the intelligence chain, command chain, mobility chain, strike chain, and support chain, and accelerating the generation of comprehensive precision-based combat capabilities.

Data-driven collaboration. The traditional operational collaboration model under hierarchical command is no longer suitable for the multi-dimensional and fast-paced nature of modern warfare. In future warfare, intelligence is key, and data is king. The deep integration of big data, cloud computing, and artificial intelligence enables the storage, analysis, fusion, and application of massive amounts of battlefield data, making command and control more scientific and operational collaboration more efficient. Leveraging powerful resource integration, computing power, and data analysis capabilities, battlefield intelligence can be rapidly integrated, battlefield situation awareness can be achieved in real time, collaborative plans can be efficiently formulated, and threat levels can be assessed instantly. This allows for the integrated planning of predicting combat actions, analyzing typical scenarios, deploying combat forces, and allocating combat resources, thereby comprehensively improving the overall effectiveness of command and control, firepower strikes, and integrated support, and driving a revolutionary change in operational collaboration.

Towards Multi-Domain Collaborative Autonomous Evolution

Future warfare will feature complex and diverse participating forces, a mix of advanced and less sophisticated weaponry, and a hybrid application of combat methods. It will exhibit distinct characteristics such as intelligent, dynamically decentralized command and control, intelligent and wide-area deployment of combat forces, and intelligent allocation and dynamic differentiation of combat missions. It is foreseeable that multi-domain联动 (interconnected and autonomous) collaboration will become a crucial component of operational coordination.

System self-restructuring and collaboration. Future warfare will involve a multi-domain battlefield space that combines virtual and real elements, with diverse military operations interacting and constraints and collaboration shifting randomly. Only an engineered and systematic organizational model can adapt to the complex needs of multi-domain collaboration. The essence of this collaboration model is to form a wide-area holographic support architecture for system self-restructuring and collaboration. Specifically, this means emphasizing the concept of system-of-systems warfare, comprehensively resolving practical contradictions in organizational system construction, institutional mechanism establishment, and collaborative rule formulation; focusing more on the system integration effect, achieving beyond-visual-range and cross-domain collaborative operations for combat units across a wide area; emphasizing efficient and flexible command, refining command relationships and clarifying command responsibilities from multiple dimensions; and paying more attention to data-driven precision, integrating network system platforms at all levels to establish a dynamic optimization network for reconnaissance, control, strike, assessment, and support missions. Once this collaboration model is formed, it will undoubtedly be able to analyze and predict typical confrontation scenarios based on the operational environment, adversaries, and missions, dynamically select action collaboration links, and plan operational actions across various domains in an integrated manner.

Tactical Adaptive Collaboration. Recent local wars have repeatedly demonstrated that the complexity and systemic nature of operational collaboration have increased exponentially due to the extension of operational data and information sharing to the tactical level. Only by achieving efficient processing, integration, and sharing of operational data and information can adaptive and autonomous collaboration among operational users be guaranteed. This collaborative model places greater emphasis on scientific planning and innovative methods to form a universal battlefield situation map with full-dimensional coverage. It supports hierarchical, cross-level, and cross-domain sharing and collaboration among users deployed across a wide area, enabling command elements and operational units to jointly perceive the battlefield situation and ensuring self-synchronous operations within a unified strategic intent, operational guidance, and collaborative planning framework. This collaborative model further emphasizes vertical integration of strategy, operations, and tactics, and horizontal integration of land, sea, air, space, and cyberspace. It provides powerful information sharing services in detection, early warning, and surveillance, and promotes the extension of operational-level joint operations to tactical-level joint operations through information media. This collaborative model further highlights the standardized operation of command and control, and the use of cutting-edge technologies such as big data and cloud computing to promote the connection of operational command levels, cross-domain linkage, element interaction, and situational awareness sharing. It achieves intelligent collaboration among command systems, weapon platforms, and sensors, and implements the key to victory through speed.

Complementary and Synergistic Advantages. In future warfare, operations in space, cyberspace, and other domains will be deeply integrated into the traditional battlefield, requiring higher standards and more stringent planning and design for the overall operation. Only by clarifying the complementary relationships and proportions of input and output across different operational domains, and then outlining the operational relationships for cross-domain collaboration, can we bridge the gaps in domain operations and achieve multi-dimensional battlefield complementarity. Essentially, this is also a concentrated reflection of the concept of war effectiveness. From another perspective, in a war, when local battlefield advantages are not obvious or harbor hidden dangers, overall victory can still be achieved by gaining local advantages in other domains to compensate and achieve comprehensive superiority. In future informationized and intelligent warfare, this will be even more prominent and complex, requiring comprehensive strategies targeting military, political, public opinion, legal, psychological, and diplomatic fields, leveraging each other to fully unleash maximum operational effectiveness; requiring close cooperation between traditional and new-type forces, building an integrated operational system based on network information systems, and maximizing overall effectiveness through synergistic advantages.

Towards Dynamic Coupling and Autonomous Collaborative Transition

In the era of artificial intelligence, with the profound changes in information technology and weaponry, combat operations place greater emphasis on breaking down traditional force formations, integrating the functions of traditional platforms, and dismantling traditional offensive and defensive boundaries, so as to achieve all-weather dynamic control of combat operations through dynamic coupling and autonomous collaboration.

Dynamic convergence and coordination. Future warfare will see more intense adversarial confrontations and more volatile battlefield situations, rendering the static, extensive, and methodical coordination methods of the past inadequate. It is imperative to pay close attention to key operational nodes, closely monitoring the overall situation, anchoring operational tasks, and focusing on operational objectives. This requires assessing the situation, seizing opportunities, and swiftly changing coordination partners, flexibly adjusting coordination strategies, and autonomously negotiating coordinated actions based on predetermined coordination rules. It is important to note that this coordination method based on key operational nodes particularly emphasizes the ability of combat forces to overcome structural barriers and organically aggregate operational effectiveness. Through the flexible structure of the coordination organization, conflicts can be self-coupled and autonomously resolved, gaps in cooperation can be bridged, and the precise release of the combined forces of the operational system can be promoted.

Dynamic control and coordination. The battlefield situation in future warfare is constantly changing, and the course of operations often deviates from the predetermined plan, resulting in significant uncertainty. This implicitly requires us to break through traditional operational thinking and closely monitor changes in the battlefield situation to implement real-time, flexible, and autonomous coordination of the operational process. This coordination method, through real-time assessment of changes in the battlefield situation, the extent of damage to enemy targets, and the scale and effectiveness of operational operations, enables rapid command and control and precise coordination in areas such as force projection, fire support, and comprehensive support, ensuring that we always maintain the initiative on the battlefield. This coordination method requires relying on advanced intelligent auxiliary means to quickly divide the operational phases, predict the duration of operational operations, analyze the overall deployment of operational forces, calculate the allocation of operational resources, and accordingly precisely control the decision-making cycle and operational rhythm, accurately coordinating troop actions and the operational process to ensure effective response to various randomness and uncertainties in combat.

Dynamic Response and Coordination. The unpredictable nature of future warfare, coupled with the profound effects of asymmetric warfare, hybrid games, and system emergence, means that planned operations will inevitably encounter various unforeseen circumstances during execution. Therefore, dynamic coordination in response to unforeseen situations is an effective strategy for resolving these contradictions. This coordination method emphasizes dynamically adjusting actions based on different situations. When unforeseen circumstances arise in a local battlefield or operation, with minimal impact on the overall operation and sufficient time, the operational system automatically responds, partially adjusting operational deployments and actions to ensure the achievement of expected operational objectives. When multiple urgent and non-urgent situations coexist on the battlefield and partially affect the overall situation, operations are dynamically and instantly coordinated according to the principle of prioritizing urgent matters, pushing the battle situation in our favor. When multiple major unexpected situations or unforeseen changes occur in the overall battle situation, coordination is carried out according to the principle of prioritizing primary directions and then secondary directions, rapidly generating new coordinated response measures to effectively address various unforeseen battlefield situations. (Wu Siliang, Jia Chunjie, Hou Yonghong)

Source: PLA Daily

(Editors: Wang Xiaoxiao, Ren Yilin)

現代國語:

2025年04月01日08:59 |

小字号

引言

作战协同是现代战争中实现体系作战、释放整体效能、达成作战目标的关键要素。近年来,随着以人工智能为代表的军事科学技术取得突破性进展,科技的赋能增效作用进一步凸显,在深刻改变战争形态、作战样式的同时,也催生出一种新的作战协同模式——自主协同。当前,应科学把握新军事革命的机遇挑战,动态统筹好自主协同发展走向,从而推动作战方式加速转型升级。

向智能赋能自主协同蜕变

未来战争将是对抗双方采用“人+智能装备”展开的全方位对抗。受军事技术、系统平台、作战能力等限制,传统作战协同因为存在周期固化、容错率低等局限,已难以适应战机转瞬即逝的现代战场。在人工智能、大数据等先进技术手段的强力支撑下,作战协同的自主性、自动化水平将极大提升,智能赋能下的自主协同亦将成为克敌制胜的关键。

广域泛在协同。近年来,通信技术、智能技术的深度发展,数据、算法、算力的积累叠加,促进了人、机、物、能的互联聚合,将军事物联网延伸扩展至态势感知、指挥控制、信火打击、后装保障等诸多领域,在促进作战能力迭代升级的同时,也为现代作战协同提供了更多选项。可以预见,军事物联网将在未来战场大放异彩,不仅是支撑作战行动的关键性基础设施,也是维系作战协同的关节枢纽。以此为依托,将催生出力量广域分散、组织模块构成、行动高度协同的泛在式作战,无时不在、无处不在、无控自主。

人机深度协同。纳卡冲突中,阿塞拜疆军队凭借无人机优势构建起强大战场优势,某种程度也宣告“机器人战争”登场。未来战争,无人机、无人车、无人舰等无人作战力量,正加速从后台支援保障走向一线作战前台,开始担当战场“主角”。较之传统作战协同,有人无人智能协同呈现出作战指挥“去中心化”、作战过程“去分工化”、技能操作高端化、前沿与后方模糊化等特点,更加强调人机协同、算法取胜。尤其是近年来,智能无人集群异军突起,开始强烈冲击现代战场。面对这些新情况新变化,应统筹运用集群编队算法、队形控制算法以及复杂场景优化算法等,推动无人与有人组网通信、智能协同,促进情报链、指挥链、机动链、打击链和保障链一体运转,加快生成精确制敌综合作战能力。

数智驱动协同。逐层递进指挥下的传统作战协同模式,已难以适应现代战争的多维度快节奏。未来战争,智能为要,数据为王。大数据、云计算、人工智能等深度融合,实现了对海量战场数据的存储、分析、融合和运用,从而使得指挥控制更加科学、作战协同更加高效。借助强大的资源整合、计算处理和数据分析能力,可以快速融合战场情报、实时感知战场态势、高效制订协同计划、瞬时评估威胁等级,将预测作战行动、解剖典型场景、布势作战力量和配置作战资源一体统筹,从而全面提升指挥控制、火力打击、综合保障等方面的综合质效,推动作战协同革命性变革。

向多域联动自主协同演进

未来战争,参战力量复杂多元、武器装备高低搭配、作战方法混合运用,呈现作战指挥智能动态分散、作战力量智联广域部署、作战任务智配动态区分等鲜明特征。可以预见,多域联动自主协同将成为作战协同的重要构成。

体系自重塑协同。未来战争多域战场空间虚实结合、多样军事行动交互作用,约束与协作随机转化,只有采取工程化、系统化的组织模式,才能适应庞杂的多域协同需要。这种协同模式,其实质是要形成体系自重塑协同的广域全息支撑架构。具体来看,就是更加突出体系作战理念,从整体上破解组织体系构建、制度机制设立、协同规则制订等现实矛盾;更加注重体系融合效应,从广域上实现作战单元超视距作战、跨域协同作战;更加强调高效灵活指挥,从诸维度细化指挥关系、厘清指挥权责;更加关注数据精准驱动,从各层级整合网络系统平台,建立侦控打评保任务动态优化网。这种协同模式一旦形成,无疑能够针对作战环境、作战对手和作战任务等,研判预测典型对抗态势场景,动态选择行动协同链路,一体规划各领域作战行动。

战术自适应协同。近年来的局部战争冲突一再表明,由于作战数据信息向战术层共享应用延伸,作战协同的复杂性系统性呈指数级跃升。只有实现作战数据信息的高效处理、融合共享,才能保证作战用户间自适应、自主化协同。这种协同模式,更加注重科学规划、创新手段,形成全维覆盖的通用战场态势图,支持广域分散部署的各级各类用户间按级、越级、跨域共享协作,实现指挥要素、作战单元共同感知战场态势,确保在统一的战略意图、战役指导、协同计划框架内自同步作战。这种协同模式,更加强调纵向贯通战略、战役、战术,横向融汇陆海空天电,在探测、预警、监视等方面提供强力信息共享服务,依托信息介质推动战役级联合向战术级联合延伸。这种协同模式,更加突出指挥运行、力量运用等的标准化运行,借助大数据、云计算等前沿技术推动作战指挥层级衔接、跨域联动、要素交互、态势共享,实现指挥系统、武器平台、传感器间的智能化协同,落地落实以快制慢制胜关键。

优势智互补协同。未来战争,太空、网络等领域作战行动深度融入传统战场空间,要求对作战全局实施更高标准更高要求的规划设计。只有搞清各作战域优势互补关联、投入成效比重,进而梳理出跨领域协同的运行关系,才能弥合领域作战缝隙,实现多维战场优势互补。从本质上看,这也是战争效益观的集中反映。从另一视角来看,一场战争,当战场局部优势不明显或暗藏危机时,通过在其他领域取得局部优势予以弥补并达成综合优势,同样可以实现整体制胜目的。未来信息化智能化战争,这一点将体现得更为突出也更为复杂,要求针对军事、政治、舆论、法理、心理、外交等领域综合施策,相互借力充分释放最大作战效能;要求传统力量、新质力量密切配合,依托网络信息体系打造一体化作战体系,通过优势协同实现整体效能最大化。

向动态耦合自主协同变迁

人工智能时代,伴随信息技术和武器装备的深度变革,作战行动更加强调打散传统力量编组、打通传统平台功能、打破传统攻防界限,通过动态耦合自主协同实现对作战行动的全时动态可控。

动态聚点协同。未来战争敌我对抗更加激烈、战场态势更为多变,以往那种静态粗放、按部就班的协同方式将难以适应。必须对作战的关键节点给予高度关注,在紧盯整体态势、锚定作战任务、聚焦作战目标的基础上,审时度势把握战机,依据预定的协同规则,敏捷变换协同对象、灵活调整协同策略、自主协商协同行动。需要注意的是,这种基于关键作战节点的协同方式,尤为强调作战力量跨越结构壁垒、有机聚合作战效能,通过协同组织的弹性结构,自耦合自主化消解矛盾冲突、弥合作战缝隙,促进作战体系合力精准释放。

动态调控协同。未来战争战场态势瞬息万变,作战进程往往难以按照预定作战计划推进,作战行动有着极大的不确定性。在无形中,这也要求我们突破传统作战思维,紧盯战场态势变化对作战进程实施即时灵活自主协同。这种协同方式,通过实时评估战场态势变化、敌方目标毁伤程度、作战行动规模效益等,从而在力量投送、火力支援、综合保障等方面实现快速指控、精准协同,始终把握战场主动权。这种协同方式,要求依托智能辅助先进手段,快速切分作战阶段,预测作战行动持续时间,研判作战力量整体布势,计算作战行动资源分配,据此精准控制决策周期和作战节奏,精准协调部队行动和作战进程,确保能够有效应对作战中的各种随机性、不确定性。

动态响应协同。未来战争作战机理变化莫测,非对称作战、混合博弈、体系涌现等的深层作用,使得预定作战方案计划在执行中必然遇到各类突发情况。为此,针对突发情况动态协同是解决上述矛盾问题的有效策略。这种协同方式,更加强调依据不同情况动态调整协同行动。当局部战场或局部行动出现突发情况,对作战全局影响不大且时间充裕时,作战体系自动响应,部分调整作战部署和作战行动,确保实现预期作战目标。当战场出现多个急缓并存情况且部分影响战场态势时,根据具体情况按照先急后缓原则动态即时协调作战行动,推动战局向着有利于我的方向发展。当战局整体发展出现多个重大意外情况或出现未曾预想的变化时,按先主要方向、后次要方向的原则展开协同,快速生成新的协同处置措施,有效应对战场各类突发情况。(吴思亮、贾春杰、侯永红)

来源:解放军报

(责编:王潇潇、任一林)

中國原創軍事資源:https://military.people.com.cn/n1/2025/0401/c1011-40451255888.html