Utile coordination: learning interdependencies among cooperative agents

Jelle R. Kok, Pieter Jan 't Hoen, Bram Bakker, and Nikos Vlassis. Utile coordination: learning interdependencies among cooperative agents. In Proceedings of the IEEE Symposium on Computational Intelligence and Games (CIG), pp. 29–36, Colchester, United Kingdom, April 2005.

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Abstract

We describe Utile Coordination, an algorithm that allows a multiagent system to learn where and how to coordinate. The method starts with uncoordinated learners and maintains statistics on expected returns. Coordination dependencies are dynamically added if the statistics indicate a statistically significant benefit. This results in a compact state representation because only necessary coordination is modeled. We apply our method within the framework of coordination graphs in which value rules represent the coordination dependencies between the agents for a specific context. The algorithm is first applied on a small illustrative problem, and next on a large predator-prey problem in which two predators have to capture a single prey.

BibTeX Entry

@InProceedings{Kok05cig,
  author =       {Jelle R. Kok and Pieter Jan 't Hoen and Bram Bakker
                  and Nikos Vlassis},
  title =        {Utile coordination: learning interdependencies among
                  cooperative agents},
  address =      {Colchester, United Kingdom},
  booktitle =    {Proceedings of the IEEE Symposium on Computational
                  Intelligence and Games (CIG)},
  year =         2005,
  month =        apr,
  pages =        {29--36},
  abstract =     {We describe Utile Coordination, an algorithm that
                  allows a multiagent system to learn where and how to
                  coordinate. The method starts with uncoordinated
                  learners and maintains statistics on expected
                  returns. Coordination dependencies are dynamically
                  added if the statistics indicate a statistically
                  significant benefit. This results in a compact state
                  representation because only necessary coordination
                  is modeled. We apply our method within the framework
                  of coordination graphs in which value rules
                  represent the coordination dependencies between the
                  agents for a specific context. The algorithm is
                  first applied on a small illustrative problem, and
                  next on a large predator-prey problem in which two
                  predators have to capture a single prey.}
}

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