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Solving Optimization Problem Using Multi-agent Model Based on Belief Interaction

  • Guo Dongwei
  • Liu Yanbin
  • Zhang Na
  • Wang Kangping
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4247)

Abstract

Multi-Agent model based on belief interaction is used to solve the function optimization problems in this paper. “Belief” is led into the Agent, being the parameter of learning machine to decide the searching direction and intensity of the Agent in the environment. It is also the interaction information between Agents. Agent has the ability to evaluate its path in the past. In this way, Agent can find optimization object rapidly and avoid partial extremum at the same time. Finally, several benchmark problems are considered to evaluate the performance of this model. The experimental results prove the efficiency of this model when solving optimization problems.

Keywords

Multi-Agent model Belief Interaction Optimization problem 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guo Dongwei
    • 1
  • Liu Yanbin
    • 1
  • Zhang Na
    • 1
  • Wang Kangping
    • 1
  1. 1.College of Computer Science & TechnologyJilin UniversityChangchunChina

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