In this paper we present the use of distributed value function techniques to reach collaboration in a multiagent system. We apply this method in two different simulation environments: a mobile robot planning/searching task and an intelligent traffic system in an urban environment. In the case of the intelligent traffic system, results show an improvement with respect to a standard fix-time controller and local adaptive controllers. Trajectories for optimal search in an obstacle environment are obtained in the mobile robot case. Some variations to the actual algorithm are pointed out to suit our cases. We conclude discussing our future work.


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    Title :

    Multi agent collaboration using distributed value functions


    Contributors:


    Publication date :

    2000-01-01


    Size :

    585286 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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