Message-Passing Algorithms for Large Structured Decentralized POMDPs

Akshat Kumar and Shlomo Zilberstein. Message-Passing Algorithms for Large Structured Decentralized POMDPs. Proceedings of the Tenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 1087-1088, Taipei, Taiwan, 2011.

Abstract

Decentralized POMDPs provide a rigorous framework for multi-agent decision-theoretic planning. However, their high complexity has limited scalability. In this work, we present a promising new class of algorithms based on probabilistic inference for infinite-horizon ND-POMDPs -- a restricted Dec-POMDP model. We first transform the policy optimization problem to that of likelihood maximization in a mixture of dynamic Bayes nets (DBNs). We then develop the Expectation-Maximization (EM) algorithm for maximizing the likelihood in this representation. The EM algorithm for ND-POMDPs lends itself naturally to a simple message-passing paradigm guided by the agent interaction graph. It is thus highly scalable w.r.t. the number of agents, can be easily parallelized, and produces good quality solutions.

Bibtex entry:

@inproceedings{KZaamas11,
  author	= {Akshat Kumar and Shlomo Zilberstein},
  title		= {Message-Passing Algorithms for Large Structured Decentralized {POMDP}s},
  booktitle     = {Proceedings of the Tenth International Conference on Autonomous
                   Agents and Multiagent Systems},
  year		= {2011},
  pages		= {1087-1088},
  address       = {Taipei, Taiwan},
  url		= {http://rbr.cs.umass.edu/shlomo/papers/KZaamas11.html}
}

shlomo@cs.umass.edu