Near-optimal anytime coalition structure generation

  • Authors:

  • Talal Rahwan;Sarvapali D. Ramchurn;Viet Dung Dang;Nicholas R. Jennings

  • Affiliations:

  • IAM Group, School of Electronics and Computer Science, University of Southampton, UK;IAM Group, School of Electronics and Computer Science, University of Southampton, UK;IAM Group, School of Electronics and Computer Science, University of Southampton, UK;IAM Group, School of Electronics and Computer Science, University of Southampton, UK

  • Venue:
  • IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
  • Year:
  • 2007

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Abstract

Forming effective coalitions is a major research challenge in the field of multi-agent systems. Central to this endeavour is the problem of determining the best set of agents that should participate in a given team. To this end, in this paper, we present a novel, anytime algorithm for coalition structure generation that is faster than previous anytime algorithms designed for this purpose. Our algorithm can generate solutions that either have a tight bound from the optimal or are optimal (depending on the objective) and works by partitioning the space in terms of a small set of elements that represent structures which contain coalitions of particular sizes. It then performs an online heuristic search that prunes the space and only considers valid and non-redundant coalition structures. We empirically show that we are able to find solutions that are, in the worst case, 99% efficient in 0.0043% of the time to find the optimal value by the state of the art dynamic programming (DP) algorithm (for 20 agents), using 66% less memory.