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Solving POMDPs using selected past events

Alain Dutech 1
1 MAIA - Autonomous intelligent machine
INRIA Lorraine, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : A new algorithm for solving Partially Observed Markov Decision Processes build on theoretical results about exhaustive observable. It aims at building an extension of the state space so as to obtain a Markov Decision Process which can then be solved by classical methods. We present two versions of the algorithm, one using reinforcement learning when the evolution model is unknown, the other is quicker but requires the knowledge of this evolution model.
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Conference papers
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https://hal.inria.fr/inria-00099378
Contributor : Publications Loria <>
Submitted on : Tuesday, September 26, 2006 - 8:53:27 AM
Last modification on : Friday, February 26, 2021 - 3:28:05 PM

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  • HAL Id : inria-00099378, version 1

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Alain Dutech. Solving POMDPs using selected past events. European Conference on Artificial Intelligence, 2000, Berlin, Germany. ⟨inria-00099378⟩

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