Modified Particle Swarm Algorithm for Decentralized Swarm Agent 2004 IEEE International Conference on Robotic and Biomimetics Dong H. Kim Seiichi Shin 林盈吟

Outline Introduction Swarm Model Description and Problem Statement Modified Particle Swarm Algorithm Simulation Examples Conclusion

Introduction Self-organization in a swarm is the ability to distribute itself “optimally” for given task. Nonlinear oscillator (2000) Behavior-based intelligences Particle Swarm Optimization

Environment and agent model

Particle Swarm optimization Representation Objective function Velocity position

Modified Particle Swarm Algorithm Velocity

Selection of p i – Fixed target – Moving target Selection of p g – Fixed target – Moving target

The relation between weighting factors and a moving target – c 3 <c 4 : leader – c 3 >c 4 : randomly

Obstacle avoidance Fitness function

Penalty function

Virtual zone

Simulation Examples The comparison of the MPSA with and without

Migration to a moving target in the existence of obstacle

Conclusion The paper presents a self-organization scheme based on the MPSA for decentralized swarm agents. This is a first attempt that the PSO concept is adapted to self-organization for swarm system.

Q&A