Identification of Optimal Policies in Markov Decision Processes

0346161 - ÚTIA 2011 RIV CZ eng J - Journal Article
Sladký, Karel
Identification of Optimal Policies in Markov Decision Processes.
Kybernetika. 46 2010, č. 3 (2010), s. 558-570. ISSN 0023-5954.
[International Conference on Mathematical Methods in Economy and Industry. České Budějovice, 15.06.2009-18.06.2009]
R&D Projects: GA ČR(CZ) GA402/08/0107; GA ČR GA402/07/1113
Institutional research plan: CEZ:AV0Z10750506
Keywords : finite state Markov decision processes * discounted and average costs * elimination of suboptimal policies
Subject RIV: BB - Applied Statistics, Operational Research
Impact factor: 0.461, year: 2010
http://library.utia.cas.cz/separaty/2010/E/sladky-identification of optimal policies in markov decision processes.pdf

In this note we focus attention on identifying optimal policies and on elimination suboptimal policies minimizing optimality criteria in discrete-time Markov decision processes with finite state space and compact action set. We present unified approach to value iteration algorithms that enables to generate lower and upper bounds on optimal values, as well as on the current policy. Using the modified value iterations it is possible to eliminate suboptimal actions and to identify an optimal policy or nearly optimal policies in a finite number of steps without knowing precise values of the performance function.
Permanent Link: http://hdl.handle.net/11104/0187257