2 research outputs found

    Learning Coordination Plans in Distributed Problem-Solving Environments

    No full text
    Coordination is an essential technique in cooperative, distributed multiagent systems. However, sophisticated coordination strategies are not always cost-effective in all problem-solving situations. This paper presents a learning method to acquire coordination plans for specific problem-solving situations so that the appropriate type of coordination strategy is used. This learning is accomplished by recording and analyzing traces of inferences after problem solving. The analysis results in identification of situations where inappropriate coordination strategies have caused redundant activities or the lack of timely execution of important activities, thus degrading system performance. Based on this identification, situationspecific coordination plans are created which use additional non-local information about activities in the networks to remedy the problem. An example from a real distributed problem-solving application involving diagnosis of a local area network is described. CFP Top..
    corecore