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arXiv · 1207.1359

MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs

Daniel Szer·Francois Charpillet·Shlomo Zilberstein
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Abstract

We present multi-agent A* (MAA*), the first complete and optimal heuristic search algorithm for solving decentralized partially-observable Markov decision problems (DEC-POMDPs) with finite horizon. The algorithm is suitable for computing optimal plans for a cooperative group of agents that operate in a stochastic environment such as multirobot coordination, network traffic control, `or distributed resource allocation. Solving such problems efiectively is a major challenge in the area of planning under uncertainty. Our solution is based on a synthesis of classical heuristic search and decentralized control theory. Experimental results show that MAA* has significant advantages. We introduce an anytime variant of MAA* and conclude with a discussion of promising extensions such as an approach to solving infinite horizon problems.

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Daniel Szer, Francois Charpillet, Shlomo Zilberstein. 2012-07-04. MAA*: A Heuristic Search Algorithm for Solving Decentralized POMDPs. https://arxiv.org/abs/1207.1359

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