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中文摘要：
本文提出了一种基于神经网络与群智能技术的多代理人决策模型。该决策模型以神经网络作为决策控制器，神经网络的输入层是代理人的历史行为策略，输出层决定了代理人的当前策略，神经网络的权重通过群智能优化技术进行训练。权重值的更新过程刻画了代理人行为策略的动态变化过程。仿真实验表明该决策模型具有自适应学习的能力，并能克服代理人之间的冲突取得Pareto最优。
英文摘要：
This paper proposes a multi-agent decision model based on neural networks and swarm intelligence technology. In this paper, a neural network is used for behavior decision controller. The inputs of the neural network are decided by the last actions of other agents. Then the outputs determine the next action that the agent will choose. The weight values are updated by swarm intelligence optimization algorithm, and they imply the behavior evolution of agents. The validity of the decision model is verified through simulation experiment, and the results show that this decision model has the ability of adaptive learning and can prevent the collision between agents to obtain the Pareto optimal.
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