| Abstract: | In this paper, an attempt has been made to incorporate 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 a swarm is based on a proportional control concept and the fitness of each agent is evaluated on-line. The virtual zone is developed to avoid conflict among the agents. In this scheme, each agent self-organizes to flock to the best agent in a swarm and migrate to a moving target while avoiding obstacles and collision among agents. Aided by these advantages such as cooperative group behaviors, flexible formation and scalability, the proposed approach enables large-scale swarm agents to distribute themselves optimally for a given task. The simulation results have shown that the proposed scheme effectively constructs a self-organized swarm system with the capability of flocking and migration. |
