Modified Particle Swarm Algorithm for Decentralized Swarm Agents
Dong Hun Kim, Seiichi Shin · 2005
In this paper, an attempt has been made by in corporating some special features in the conventional particle swarm optimization (PSO) technique for decentralized swarm agents. The modified particle swarm algorithm (MPSA) for the self-organization of decentralized swarm agents is proposed and studied. In the MPSA, the update rule of the best agent in swarm is based on a proportional control concept and the fitness of each agent is evaluated on-line. In this scheme, each agent self organizes to flock to the best agent in swarm and migrate to a moving target while avoiding collision between the agent and the nearest obstacle/agent. The simulation results have shown that the proposed scheme effectively constructs a self-organized swarm system in the capability of the flocking and migration.