A New Optimality Criterion for Nonhomogeneous Markov Decision Processes

Wallace J. Hopp, James C. Bean and Robert L. Smith
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Wallace J. Hopp: Northwestern University, Evanston, Illinois
James C. Bean: The University of Michigan, Ann Arbor, Michigan
Robert L. Smith: The University of Michigan, Ann Arbor, Michigan

Operations Research, 1987, vol. 35, issue 6, 875-883

Abstract: We propose a new definition of optimality for nonhomogeneous Markov decision processes called periodic forecast horizon (PFH) optimality. Using measures of discounting and ergodicity, we establish conditions under which PFH-optimal strategies exist and PFH optimality implies the more conventional notions of α-optimality and average optimality. Finally, we use this definition of optimality as the basis for a direct development of forecast horizon results for discounted and undiscounted nonhomogeneous Markov decision processes.

Keywords: 118 computations for nonhomogeneous chains; 626 new optimality criterion (search for similar items in EconPapers)
Date: 1987
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