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

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.