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Improved bound on the worst case complexity of Policy Iteration

Hollanders, Romain and Gerencsér, Balázs and Delvenne, Jean-Charles and Jungers, Raphaël M. (2016) Improved bound on the worst case complexity of Policy Iteration. OPERATIONS RESEARCH LETTERS, 44 (2). pp. 267-272. ISSN 0167-6377

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Abstract

Solving Markov Decision Processes is a recurrent task in engineering which can be performed efficiently in practice using the Policy Iteration algorithm. Regarding its complexity, both lower and upper bounds are known to be exponential (but far apart) in the size of the problem. In this work, we provide the first improvement over the now standard upper bound from Mansour and Singh (1999). We also show that this bound is tight for a natural relaxation of the problem.

Item Type: Article
Uncontrolled Keywords: Acyclic Unique Sink Orientation; Factored Markov decision process; COMPLEXITY; Policy iteration
Subjects: Q Science / természettudomány > QA Mathematics / matematika
SWORD Depositor: MTMT SWORD
Depositing User: MTMT SWORD
Date Deposited: 03 Jan 2017 17:26
Last Modified: 03 Jan 2017 17:26
URI: http://real.mtak.hu/id/eprint/44200

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