Distributed decision making of robotic agents

Jelle R. Kok and Nikos Vlassis. Distributed decision making of robotic agents. In Proceedings of the 9th Annual Conference of the Advanced School for Computing and Imaging, Heijen, The Netherlands, pp. 318–325, Advanced School for Computing and Imaging (ASCI), June 2003.

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Abstract

In order to make a distributed decision in a group of agents, each agent has to take into account the actions of the agents on which it depends. In a dynamic environment, these dependencies may change rapidly as a result of the continuously changing state. Coordination graphs offer a scalable solution to the problem of multiagent coordination by decomposing the problem into smaller subproblems. In this paper, we show how coordination graphs can be applied to dynamic and continuous domains by assigning roles to the agents and then coordinating the different roles. Moreover, we show how an agent can predict the action of the other agents, making communication unnecessary. Finally, we will demonstrate this method on the RoboCup soccer simulation domain.

BibTeX Entry

@InProceedings{ Kok03asci,
  author =       {Jelle R. Kok and Nikos Vlassis},
  title =        {Distributed decision making of robotic agents},
  booktitle =    {Proceedings of the 9th Annual Conference of the
                  Advanced School for Computing and Imaging, Heijen,
                  The Netherlands},
  publisher =    {Advanced School for Computing and Imaging (ASCI)},
  editor =       {S. Vassiliadis and L.M.J. Florack and
                  J.W.J. Heijnsdijk and A. van der Steen},
  pages =        {318--325},
  year =         {2003},
  month =        jun,
  postscript =   {2003/Kok03asci.ps.gz},
  pdf =          {2003/Kok03asci.pdf},
  abstract =     {In order to make a distributed decision in a group
                  of agents, each agent has to take into account the
                  actions of the agents on which it depends. In a
                  dynamic environment, these dependencies may change
                  rapidly as a result of the continuously changing
                  state. Coordination graphs offer a scalable solution
                  to the problem of multiagent coordination by
                  decomposing the problem into smaller subproblems. In
                  this paper, we show how coordination graphs can be
                  applied to dynamic and continuous domains by
                  assigning roles to the agents and then coordinating
                  the different roles. Moreover, we show how an agent
                  can predict the action of the other agents, making
                  communication unnecessary. Finally, we will
                  demonstrate this method on the RoboCup soccer
                  simulation domain.}
}

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