ASYMPTOTIC OPTIMALITY AND RATES OF CONVERGENCE OF QUANTIZED STATIONARY POLICIES IN CONTINUOUS-TIME MARKOV DECISION PROCESSES

Asymptotic Optimality and Rates of Convergence of Quantized Stationary Policies in Continuous-Time Markov Decision Processes

This paper is concerned with the asymptotic optimality of quantized stationary policies for continuous-time Markov decision processes (CTMDPs) in Polish spaces with state-dependent discount factors, lock shock and barrel art where the transition rates and reward rates are allowed to be unbounded.Using the dynamic programming approach, we first esta

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