Solving Optimization Problem Using Multi-agent Model Based on Belief Interaction
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.
KeywordsMulti-Agent model Belief Interaction Optimization problem
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