Optimization and Distributed Execution of MAS Cooperative Strategy Based on Factored Dec-MDP
Yuan Yuan · 2009
The complexity of MAS cooperation strategy in uncertain environment determines the success of cooperation task.In order to reduce the complexity created by factored MDP model and the cooperation traffic,the method of creating strategy tree by the model was improved.Using the context-specific and conditional independence existing among the agent states in Bayesian network,the tree created by SPI algorithm was decomposed and optimized.This makes the independent agents in MAS running independently,and only communicating with each other when cooperation is needed,where the Peer-to-Peer method is applied.Simulation indicates that MAS applying the strategy not only accomplishes the task and gains the reward,but effectively reduces traffic simultaneously.