An integrated token-based algorithm for scalable coordination

  • Authors:

  • Yang Xu;Paul Scerri;Bin Yu;Steven Okamoto;Michael Lewis;Katia Sycara

  • Affiliations:

  • University of Pittsburgh;Carnegie Mellon University;Carnegie Mellon University;Carnegie Mellon University;University of Pittsburgh;Carnegie Mellon University

  • Venue:
  • Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
  • Year:
  • 2005

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Abstract

Efficient coordination among large numbers of heterogeneous agents promises to revolutionize the way in which some complex tasks, such as responding to urban disasters can be performed. However, state of the art coordination algorithms are not capable of achieving efficient and effective coordination when a team is very large. Building on recent successful token-based algorithms for task allocation and information sharing, we have developed an integrated and efficient approach to effective coordination of large scale teams. We use tokens to encapsulate anything that needs to be shared by the team, including information, tasks and resources. The tokens are efficiently routed through the team via the use of local decision theoretic models. Each token is used to improve the routing of other tokens leading to a dramatic performance improvement when the algorithms work together. We present results from an implementation of this approach which demonstrates its ability to coordinate large teams.