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The communicative multiagent team decision problem: analyzing teamwork theories and models
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Exploiting locality of interaction in factored Dec-POMDPs
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Solving Large-Scale and Sparse-Reward DEC-POMDPs with Correlation-MDPs
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Toward error-bounded algorithms for infinite-horizon DEC-POMDPs
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Solving decentralized POMDP problems using genetic algorithms
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Approximate solutions for factored Dec-POMDPs with many agents
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In this work, we suggest representing multiagent systems using computational models, choosing, specifically, Multi-Prover Interactive Protocols to represent agent systems and the interactions occurring within them. This approach enables us to analyze complexity issues related to multiagent systems. We focus here on the complexity of coordination and study the possible sources of this complexity. We show that there are complexity bounds that cannot be lowered even when approximation techniques are applied.