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See detailNon-communicative multi-robot coordination in dynamic environments
Kok, J. R.; Spaan, M. T. J.; Vlassis, Nikos UL

in Robotics & Autonomous Systems (2005), 50(2-3), 99-114

Within a group of cooperating agents the decision making of an individual agent depends on the actions of the other agents. In dynamic environments, these dependencies will change rapidly as a result of ... [more ▼]

Within a group of cooperating agents the decision making of an individual agent depends on the actions of the other agents. In dynamic environments, these dependencies will change rapidly as a result of the continuously changing state. Via a context-specific decomposition of the problem into smaller subproblems, coordination graphs offer scalable solutions to the problem of multiagent decision making. In this work, we apply coordination graphs to a continuous (robotic) domain by assigning roles to the agents and then coordinating the different roles. Moreover, we demonstrate that, with some additional assumptions, an agent can predict the actions of the other agents, rendering communication superfluous. We have successfully implemented the proposed method into our UvA Trilearn simulated robot soccer team which won the RoboCup-2003 World Championship in Padova, Italy. (C) 2004 Elsevier B.V. All rights reserved. [less ▲]

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See detailAnytime Algorithms for Multiagent Decision Making Using Coordination Graphs
Vlassis, Nikos UL; Elhorst, R.; Kok, J. R.

in Proceedings of the International Conference on Systems, Man and Cybernetics (2004)

Coordinationgraphsprovideatractableframe- work for cooperative multiagent decision making by decom- posing the global payoff function into a sum of local terms. In this paper we review some distributed ... [more ▼]

Coordinationgraphsprovideatractableframe- work for cooperative multiagent decision making by decom- posing the global payoff function into a sum of local terms. In this paper we review some distributed algorithms for ac- tion selection in a coordination graph and discuss their pros and cons. For real-time decision making we emphasize the need for anytime algorithms for action selection: these are algorithms that improve the quality of the solution over time. We describe variable elimination, coordinate ascent, and the max-plus algorithm, the latter being an instance of the be- lief propagation algorithm in Bayesian networks. We discuss some interesting open problems related to the use of the max- plus algorithm in real-time multiagent decision making. [less ▲]

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