Decision-making and Simulation in Multi-agent System Based on Neural Network and PSO

摘要：

This paper proposes a method using neural networks and particle swarm optimization (PSO) for the decision-making in the multi-agent system. In this paper, a neural network is used for behavior decision controller.The input of the neural network is decided by the last strategies of other agents. The output determines the next strategy that the agent will choose. The connection weight values of this neural network are encoded as fitness, and the weight values are updated using the particle swarm optimization algorithm. Here, the weight values imply the adaptiveness of agents in multi-agent system. The validity of the decision model is verified through simulation.Experimental results show that the decision model can successfully simulate agents dynamic learning and make agents choose the appropriate strategies.

关键词： Decision-making Multi-agent system Neural network PSO

作者: Liang Peng Haiyun Liu

作者单位: School of Economics, Huazhong University of Science and Technology Wuhan, China

会议类型: 国际会议

会议名称: 2007 Conference on Systems Science, Management Science and System Dynamics(第二届系统科学、管理科学与系统动力学国际会议)

会议地点: 上海

会议语种:英文

页码: 1671-1676

在线出版日期: 2007-10-19（万方平台首次上网日期，不代表论文的发表时间）