1. Modified Particle Swarm Algorithm for Decentralized Swarm Agent 2004 IEEE International Conference on Robotic and Biomimetics Dong H. Kim Seiichi Shin 9457515 林盈吟

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

3. 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

4. Environment and agent model

5. Particle Swarm optimization Representation Objective function Velocity position

6. Modified Particle Swarm Algorithm Velocity

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

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

9. Obstacle avoidance Fitness function

10. Penalty function

11. Virtual zone

12. Simulation Examples The comparison of the MPSA with and without

14. Migration to a moving target in the existence of obstacle

15. 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.

16. Q&A