A PSO solution for pursuit-evasion problem of randomly mobile agents

  • Authors:

  • Jiancong Fan;Jiuhong Ruan;Yongquan Liang;Leiyu Tang

  • Affiliations:

  • College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, China;Scientific Research Department, Shandong Jiaotong University, Jinan, China;College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, China;College of Information Science and Engineering, Shandong University of Science and Technology, Qingdao, China and College of Science, Shandong University of Science and Technology, Qingdao, China

  • Venue:
  • CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
  • Year:
  • 2009

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Abstract

Pursuit-evasion problem is a process that one or several agents pursuit one or several other agents. The persuading agents and evading agents are regarded as mobile intelligent agents. These intelligent agents are considered as perspicacious particles to solve the pursuit-evasion problem. The moving trajectory of evading particles is partitioned into local moving functions. By particle swarm optimization(PSO) algorithm the pursuit particles solve these local functions. The function value that most close to evading particles is the local best value. The global best value can be obtained when evading particle is captured. Experiments show that pursuit-evasion solving based on PSO has better time performance, and with capture action areas increasing the capture time increases linearly.