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Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions

Frans A. Oliehoek, Matthijs T. J. Spaan, and Stefan J. Witwicki. Factored Upper Bounds for Multiagent Planning Problems under Uncertainty with Non-Factored Value Functions. In Proc. of International Joint Conference on Artificial Intelligence, pp. 1645–1651, 2015.

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Abstract

Nowadays, multiagent planning under uncertainty scales to tens or even hundreds of agents. However, current methods either are restricted to problems with factored value functions, or provide solutions without any guarantees on quality. Methods in the former category typically build on heuristic search using upper bounds on the value function. Unfortunately, no techniques exist to compute such upper bounds for problems with non-factored value functions, which would additionally allow for meaningful benchmarking of methods of the latter category. To mitigate this problem, this paper introduces a family of influence-optimistic upper bounds for factored Dec-POMDPs without factored value functions. We demonstrate how we can achieve firm quality guarantees for problems with hundreds of agents.

BibTeX Entry

@InProceedings{Oliehoek15ijcai,
  author =       {Frans A. Oliehoek and Matthijs T. J. Spaan and
                  Stefan J. Witwicki},
  title =        {Factored Upper Bounds for Multiagent Planning
                  Problems under Uncertainty with Non-Factored Value
                  Functions},
  booktitle =    {Proc. of International Joint Conference on
                  Artificial Intelligence},
  year =         2015,
  pages =        {1645--1651}
}

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