An Alliance Generation Algorithm Based on Modified Particle Swarm Optimization for Multiple Emotional Robots Pursuit-evader Problem

摘要：

　　This paper researches the alliance generation algorithm with emotional factors on the basis of multiple robots pursuit-evader problem.Firstly,this paper constructs an emotional model for pursuit robots: we not only apply the basic emotion method to the emotional expression,but also simulate the process of emotional transfer with Hidden Markov Model(HMM).Secondly,we determine the cooperation intention according to the robots emotional factors,so that we can prevent the robots with the negative emotions from involving in the mission in case of a negative impact on the alliance.Then,we introduce the subgroup size on the foundation of particle swarm optimization(PSO)to avoid the premature convergence problem,thus the algorithm can obtain the maximum profit in a relatively short period of time.Finally,we bring in the dynamic redistribution mechanism for a better pursuit efficiency.

关键词： emotional robot multiple robots pursuit-evader problem alliance generation algorithm PSO algorithm dynamic redistribution mechanism

作者: Hao Wang Cheng Luo Baofu Fang

作者单位: Hefei University of Technology Hefei, China

会议类型: 国际会议

会议名称: The 2014 10th International Conference on Natural Computation (ICNC 2014) and the 2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014)(第十届自然计算和第十一届模糊系统与知识发现国际会议)

会议地点: 厦门

会议语种:英文

页码: 898-903

在线出版日期: 2014-08-19（万方平台首次上网日期，不代表论文的发表时间）