Real world multi-agent systems: information sharing, coordination and planning

F.C.A Groen, M.T.J. Spaan, and J.R. Kok. Real world multi-agent systems: information sharing, coordination and planning. In Proceedings of the Workshop ICT Agents, The Hague, The Netherlands, November 2004.

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Abstract

Applying multiagent systems in real world scenarios requires some essential research questions to be answered. International challens play an important role in comparing different approaches to these questions. One such a challenge in this field is RoboCup. In this paper we focus on three of these research questions: A shared world model which estimates the global positions of objects in order to reduce the uncertainty in the environment. It allows us to fuse observations made by different agents and improve position estimates of each agent. Second, we show how coordination graphs can be applied to multi-robot teams to allow for efficient coordination. Third, we present work in the POMDP framework for agent planning in uncertain environments, in which the agent only receives partial information (through its sensors) regarding the true state of environment.

BibTeX Entry

@InProceedings{Groen04ictagents,
  author =       {F.C.A Groen and M.T.J. Spaan and J.R. Kok},
  title =        {Real world multi-agent systems: information sharing,
                  coordination and planning},
  booktitle =    {Proceedings of the Workshop ICT Agents},
  address =      {The Hague, The Netherlands},
  month =        nov,
  year =         {2004},
  abstract =     {Applying multiagent systems in real world scenarios
                  requires some essential research questions to be
                  answered. International challens play an important
                  role in comparing different approaches to these
                  questions. One such a challenge in this field is
                  RoboCup. In this paper we focus on three of these
                  research questions: A shared world model which
                  estimates the global positions of objects in order
                  to reduce the uncertainty in the environment. It
                  allows us to fuse observations made by different
                  agents and improve position estimates of each
                  agent. Second, we show how coordination graphs can
                  be applied to multi-robot teams to allow for
                  efficient coordination. Third, we present work in
                  the POMDP framework for agent planning in uncertain
                  environments, in which the agent only receives
                  partial information (through its sensors) regarding
                  the true state of environment.}
}

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