Technical Note: On Ordinal Comparison of Policies in Markov Reward Processes

H. S. Chang
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H. S. Chang: Sogang University

Journal of Optimization Theory and Applications, 2004, vol. 122, issue 1, No 9, 207-217

Abstract: Abstract An asymptotic exponential convergence rate of ordinal comparison from large deviations theory is well known for selecting the true best solution from the candidate solutions sample means. This note supplements the theories developed by Dai within the framework of ergodic Markov reward processes for ε-ordinal comparison of policies, establishing an asymptotic exponential convergence rate for the infinite-horizon average criterion.

Keywords: Ordinal comparisons; large deviations; stochastic simulations; Markov reward processes (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1023/B:JOTA.0000041736.82051.f1

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