提出一套AI驱动的军事行动方案自动生成系统架构。
Architecture of an AI-Based Automated Course of Action Generation System for Military Operations
- 基于公开信息梳理行动方案规划各阶段的AI技术应用。
- 构建可扩展的自动化行动方案生成系统框架。
- 适合军事AI研发与作战系统设计人员参考。
未来战争中，行动方案（CoA）规划的自动化至关重要。随着机动速度提升、侦察范围扩大和武器射程增加，作战区域不断扩展，传统人工主导的行动方案规划愈发困难。因此，发展基于人工智能的自动化行动方案规划系统日益必要。目前，多个国家和国防机构正积极研发此类系统。然而，受安全限制和公开披露不足影响，相关技术成熟度难以评估，具体实现细节也鲜有公开，制约了对当前发展水平的准确判断。为此，本研究在公开信息范围内梳理相关作战理论，并针对行动方案规划的各个阶段，提出适用的AI技术路径。最终，提出一个自动化行动方案生成系统的整体架构，为后续研发提供参考。
原文摘要 · Abstract (English)
The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges extend, and weapon ranges grow, the operational area expands, making traditional manned-based CoA planning increasingly challenging. Consequently, the development of an AI-based automated CoA planning system is becoming increasingly necessary. Accordingly, several countries and defense organizations are actively developing AI-based CoA planning systems. However, due to security restrictions and limited public disclosure, the technical maturity of such systems remains difficult to assess. Furthermore, as these systems are military-related, their details are not publicly disclosed, making it difficult to accurately assess the current level of development. In response to this, this study aims to introduce relevant doctrines within the scope of publicly available information and present applicable AI technologies for each stage of the CoA planning process. Ultimately, it proposes an architecture for the development of an automated CoA planning system.
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