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Intelligent task planning and action selection of a mobile robot in a multi-agent system through a fuzzy neural network approach

机译:基于模糊神经网络的多主体系统移动机器人智能任务规划与动作选择

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This paper proposes an intelligent task planning and action selection mechanism for a mobile robot in a robot soccer system through a fuzzy neural network approach. The proposed fuzzy neural network system is developed through the two dimensional fuzzification of the soccer field. A five layer fuzzy neural network system is trained through error back propagation learning algorithm to impart a strategy based action selection. The action selection depends on the field configuration, and the emergence of a particular field configuration results from the game dynamics. Strategy of the robot changes when the configuration of the objects in the field changes. The proposed fuzzy neural network structure is flexible to accommodate all possible filed configurations. Simulation results indicate that the proposed approach is simple and has the capability in coordinating the multi-agent system through selection of sensible actions.
机译:通过模糊神经网络方法,提出了足球机器人系统中移动机器人的智能任务计划和动作选择机制。该模糊神经网络系统是通过对足球场进行二维模糊化而开发的。通过错误反向传播学习算法训练五层模糊神经网络系统,以赋予基于策略的动作选择。动作选择取决于场地配置,并且特定场地配置的出现是由游戏动态引起的。当现场对象的配置发生更改时,机器人的策略也会更改。所提出的模糊神经网络结构可以灵活地适应所有可能的字段配置。仿真结果表明,该方法简单易行,具有通过选择合理的动作来协调多智能体系统的能力。

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