Technical Note—Identifying Forecast Horizons in Nonhomogeneous Markov Decision Processes
Operations Research · 1989 · Volume 37 · Issue 2
Abstract
A procedure for identifying forecast horizons in nonhomogeneous Markov decision processes, based on convergence results for relative value functions, is developed. Two different algorithmic implementations of this procedure are discussed, and a closed form expression for computing sufficiently long horizons to guarantee epsilon optimality is presented.
Keywords
dynamic programming, Markov finite state: nonhomogeneous Markov decision processes, programming, infinite dimensional: infinite horizon optimization
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