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Using Cognitive Behavioral Learning in Multi-agent Pursuit-Evasion Game

机译:在多智能体逃避游戏中使用认知行为学习

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It is a challenging problem that Multi-Agent systemmake the best response action in a dynamic environment. This study applied probabilistic theory and Piaget's schema theory to develop a cognitive behavioral learning mechanism for the pursuit-evasion game in a dynamic environment. The proposed cognitive schema is divided into two parts, one is a perceptional schema and the other is an intentional schema. According to the agent's state, intentional schema applied probabilistic theory to propose three strategies for prediction of the evader's position in a dynamic environment. Perceptional schema applied case base dreasoning to select the adequate action for the pursuitagent. When an agent faces a new situation, it might useassimilation mechanism to deal with the problem. If the currentcognitive schema cannot explain their environment, accommodation mechanism is used to adapt the cognitive schema of the agent for dealing with their problem.
机译:Multi-Agent系统在动态环境中做出最佳响应动作是一个具有挑战性的问题。本研究运用概率论和皮亚杰图式理论为动态环境下的逃避游戏开发了一种认知行为学习机制。所提出的认知图式分为两部分,一个是感知图式,另一个是有意图式。根据主体的状态,有意图式应用了概率理论,提出了三种策略来预测动态环境中逃避者的位置。感知模式应用案例库推理来为追踪代理选择适当的动作。当代理面对新情况时,可能会使用同化机制来解决问题。如果当前的认知模式无法解释其环境,则使用适应机制来调整主体的认知模式以处理其问题。

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