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ATAL
2008
Springer

Exploiting locality of interaction in factored Dec-POMDPs

8 years 4 months ago
Exploiting locality of interaction in factored Dec-POMDPs
Decentralized partially observable Markov decision processes (Dec-POMDPs) constitute an expressive framework for multiagent planning under uncertainty, but solving them is provably intractable. We demonstrate how their scalability can be improved by exploiting locality of interaction between agents in a factored representation. Factored Dec-POMDP representations have been proposed before, but only for DecPOMDPs whose transition and observation models are fully independent. Such strong assumptions simplify the planning problem, but result in models with limited applicability. By contrast, we consider general factored Dec-POMDPs for which we analyze the model dependencies over space (locality of interaction) and time (horizon of the problem). We also present a formulation of decomposable value functions. Together, our results allow us to exploit the problem structure as well as heuristics in a single framework that is based on collaborative graphical Bayesian games (CGBGs). A preliminar...
Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Wh
Added 12 Oct 2010
Updated 12 Oct 2010
Type Conference
Year 2008
Where ATAL
Authors Frans A. Oliehoek, Matthijs T. J. Spaan, Shimon Whiteson, Nikos A. Vlassis
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