Optimal adaptive policies for markov decision processes - Burnetas, AN; Katehakis, M.N. (Mathematics of Operations Research, 1997)
In this paper we consider the problem of adaptive control for Markov Decision Processes. We give the explicit form for a class of adaptive policies that possess optimal increase rate properties for the total expected finite horizon reward, under sufficient assumptions of finite state-action spaces and irreducibility of the transition law. A main feature of the proposed policies is that the choice of actions, at each state and time period, is based on indices that are inflations of the right-hand side of the estimated average reward optimality equations.
Keywords: Adaptive control systems; Decision theory; Dynamic programming; Estimation; Markov processes; Markovian decision process (MDP); Multi armed bandit (MAB) problem; Optimal control systems; Process control; State space methods; Statistics