Nonstationary value-iteration and adaptive control of discounted semi- Markov processes
We consider in this paper discounted-reward, denumerable state space, semi-Markov decision processes which depend on unknown parameters. The problems we are interested in are: Given that the true parameter value is unknown, (I) give an iterative scheme to determine the total maximal discounted reward, and (II) find an asymptotically discount optimal (adaptive) policy. Our solutions are inspired by the nonstationary value iteration (NVI) scheme of \textit{A. Federgruen} and \textit{P. J. Schweitzer} [J. Optimization Theory Appl. 34, 207-241 (1981; Zbl 0426.90091)] combined with the ideas of \textit{M. Schäl} [in: Optimization, theory and algorithms, Conf. Confolant/France 1981, Lect. Notes Pure Appl. Math. 86, 239-253 (1983; Zbl 0525.93071)] concerning the ''principle of estimation and control'' for the adaptive control of semi-Markov processes.
adaptive control of semi-Markov processes
scientific article; zbMATH DE number 3930759
scientific article