DocumentCode
810207
Title
Markov decision Processes with fractional costs
Author
Ren, Zhiyuan ; Krogh, Bruce H.
Author_Institution
Signal Electron. & Embedded Syst. Lab., Gen. Electr. Global Res. Center, Niskayuna, NY, USA
Volume
50
Issue
5
fYear
2005
fDate
5/1/2005 12:00:00 AM
Firstpage
646
Lastpage
650
Abstract
Certain methods for constructing embedded Markov decision processes (MDPs) lead to performance measures that are the ratio of two long-run averages. For such MDPs with finite state and action spaces and under an ergodicity assumption, this note presents algorithms for computing optimal policies based on policy iterations, linear programming, value iterations and Q-learning.
Keywords
Markov processes; iterative methods; linear programming; Q-learning; embedded Markov decision processes; ergodicity assumption; fractional costs; linear programming; optimal policy computation; policy iterations; value iterations; Cost function; Embedded system; Linear programming; Probability; Q factor; State-space methods; Fractional costs; Markov decision processes;
fLanguage
English
Journal_Title
Automatic Control, IEEE Transactions on
Publisher
ieee
ISSN
0018-9286
Type
jour
DOI
10.1109/TAC.2005.846520
Filename
1431043
Link To Document