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基于案例和MAX-MIN云推理的UCAV双层战术决策

     

摘要

针对无人作战飞机空战过程中的战术决策问题,借鉴认知心理学双重加工理论,提出了一种案例推理与MAX-MIN云推理机制相结合的双层战术决策方案.首先,将飞行员作战经验案例化以构建案例库,将问题情境和案例库中的源案例进行相似度匹配以实现第一层基于案例推理的启发式决策,若是低于相似度阈值则转向第二层基于MAX-MIN云推理的分析决策,用前件云发生器对空战特征属性云化以形成属性云滴;然后,结合定性规则,采用MAX-MIN云推理算法得到规则云滴,进而得出战术决策方案.仿真结果表明,提出的双层战术决策可有效实现无人作战飞机空战战术决策,决策时间符合空战实时性要求.%To solve the problem in tactical decision-making of Unmanned Combat Aerial Vehicles (UCAVs) in air combat, and inspired by the dual-process theory in cognitive psychology, we proposed a double-layer tactical decision-making strategy based on Case Based Reasoning (CBR) and MAX-MIN cloud reasoning. Firstly, the experience of pilots was converted into cases to construct a case library, and the first-layer heuristic decision-making based on CBR was achieved by matching the degree of similarity between problem situations and original cases from case libraries. If the degree of similarity was lower than the threshold, it would turn to the second layer, the decision-making based on MAX-MIN cloud reasoning. The characteristic attributes concerning air combating were converted into cloud drops of attributes, then the cloud drops of combating rules was derived with the help of MAX-MIN cloud reasoning algorithm, and furthermore the tactical decision scheme was obtained. The simulation result showed that the double-layer method can implement decision-making effectively, and the time cost for decision-making satisfies the realtime request.

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