为机械化部队生成并评估多种作战方案，动态支持战场决策。
Autonomous generation of different courses of action in mechanized combat operations
- 通过系统生成数千种行动方案，结合对手状态动态评估。
- 基于兵力构成、攻防类型和推进速度等条件优化方案效果。
- 适合军事指挥决策支持，尤其在复杂战场环境下的快速应变。
本文提出一种方法，用于支持机械化步兵部队在地面作战执行阶段的决策，重点在于制定自身行动方案。该方法从初始方案集出发，依据预期结果进行评估，系统生成数千种独立行动选项，并通过评估筛选出表现更优的替代方案。评估综合考虑敌方态势、部队组成、兵力比、进攻/防御类型及预期推进速度，参考作战手册对战斗结果和推进速率进行判定。生成与评估过程并行进行，形成多样化行动选项。该方法可基于已有评估结果持续生成新方案，随着战况变化，在序贯决策框架下为指挥员提供更新的行动建议。
原文摘要 · Abstract (English)
In this paper, we propose a methodology designed to support decision-making during the execution phase of military ground combat operations, with a focus on one's actions. This methodology generates and evaluates recommendations for various courses of action for a mechanized battalion, commencing with an initial set assessed by their anticipated outcomes. It systematically produces thousands of individual action alternatives, followed by evaluations aimed at identifying alternative courses of action with superior outcomes. These alternatives are appraised in light of the opponent's status and actions, considering unit composition, force ratios, types of offense and defense, and anticipated advance rates. Field manuals evaluate battle outcomes and advancement rates. The processes of generation and evaluation work concurrently, yielding a variety of alternative courses of action. This approach facilitates the management of new course generation based on previously evaluated actions. As the combat unfolds and conditions evolve, revised courses of action are formulated for the decision-maker within a sequential decision-making framework.
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