Earticle

초록

영어

How to generate the task-oriented optimal agent coalition is a key issue of multi-agent system, which is a typical optimization problem. In this paper, an improved particle swarm optimization (IPSO) is proposed to solve this problem. In order to overcome the premature and local optimization problem in traditional particle swarm optimization (PSO), we proposed a variation of inertia weight PSO algorithm by analyzing the feasibility of particle optimization process in PSO. Compared with several well-known algorithms such as PSO, ACO, experimental results show that the global search capability of IPSO has been significantly improved and IPSO can effectively avoid premature convergence problem. Also it can solve the multi-agent coalition formation problem effectively and efficiently.

목차

Abstract
 1. Introduction
 2. Background
  2.1 Model for Coalition Formation
  2.2 Particle Swarm Optimization
 3. Improved Particle Swarm Optimization (IPSO)
  3.1. Improving Ideological
  3.2. The Calculation of the Fitness of the Particle
  3.3. The Procedure of PSO
 4. Experimental Results and Analysis
 5. Conclusion
 Acknowledgements
 References

키워드

저자

• Bo Xu [ Department of Computer Science and Technology, Guangdong University of Petrochemical Technology, Guangdong, China ]
• Zhaofeng Yang [ Software Engineering School of Pingdingshan University, Henan, China ]
• Yu Ge [ College of Fundamental, Sichuan Normal University, Chengdu, China ]
• Zhiping Peng [ Department of Computer Science and Technology, Guangdong University of Petrochemical Technology, Guangdong, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605