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Algebra and Geometry Through Hamiltonian Systems Read chapter Read first chapter

2014 | OriginalPaper | Chapter

18. Optimality Conditions for Partially Observable Markov Decision Processes

Authors : Eugene A. Feinberg, Pavlo O. Kasyanov, Mikhail Z. Zgurovsky

Published in: Continuous and Distributed Systems

Publisher: Springer International Publishing

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Abstract

This note describes sufficient conditions for the existence of optimal policies for Partially Observable Markov Decision Processes (POMDPs). The objective criterion is either minimization of total discounted costs or minimization of total nonnegative costs. It is well-known that a POMDP can be reduced to a Completely Observable Markov Decision Process (COMDP) with the state space being the sets of believe probabilities for the POMDP. Thus, a policy is optimal in POMDP if and only if it corresponds to an optimal policy in the COMDP. Here we provide sufficient conditions for the existence of optimal policies for COMDP and therefore for POMDP.

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previous chapter On the Regularities of Mass Random Phenomena
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Metadata
Title
Optimality Conditions for Partially Observable Markov Decision Processes
Authors
Eugene A. Feinberg
Pavlo O. Kasyanov
Mikhail Z. Zgurovsky
Copyright Year
2014
Book
Continuous and Distributed Systems

Print ISBN: 978-3-319-03145-3

Electronic ISBN: 978-3-319-03146-0

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-03146-0_18