Denumerable state semi-Markov decision processes with unbounded costs, average cost criterion
نویسندگان
چکیده
منابع مشابه
Denumerable Undiscounted Semi-Markov Decision Processes with Unbounded Rewards
This paper establishes the existence of a solution to the optimality equations in undiscounted semi-Markov decision models with countable state space, under conditions generalizing the hitherto obtained results. In particular, we merely require the existence of a finite set of states in which every pair of states can reach each other via some stationary policy, instead of the traditional and re...
متن کاملDenumerable controlled Markov chains with strong average optimality criterion: Bounded & unbounded costs
This paper studies discrete-time nonlinear controlled stochastic systems, modeled by controlled Markov chains (CMC) with denumerable state space and compact action space, and with an infinite planning horizon. Recently, there has been a renewed interest in CMC with a long-run, expected average cost (AC) optimality criterion. A classical approach to study average optimality consists in formulati...
متن کاملl AVERAGE COST SEMI - MARKOV DECISION PROCESSES
^ The Semi-Markov Decision model is considered under the criterion of long-run average cost. A new criterion, which for any policy considers the limit of the expected cost Incurred during the first n transitions divided by the expected length of the first n transitions, is considered. Conditions guaranteeing that an optimal stationary (nonrandomized) policy exist are then presented. It is also ...
متن کاملDenumerable State Nonhomogeneous Markov Decision Processes
We consider denumerable state nonhomogeneous Markov decision processes and extend results from both denumerable state homogeneous and finite state nonhomogeneous problems. We show that, under weak ergodicity, accumulation points of finite horizon optima (termed algorithmic optima) are average cost optimal. We also establish the existence of solution horizons. Finally, an algorithm is presented ...
متن کاملNonparametric Adaptive Control for Discrete - Time Markov Processes with Unbounded Costs under Average Criterion
We introduce average cost optimal adaptive policies in a class of discrete-time Markov control processes with Borel state and action spaces, allowing unbounded costs. The processes evolve according to the system equations xt+1 = F (xt, at, ξt), t = 1, 2, . . . , with i.i.d. R -valued random vectors ξt, which are observable but whose density ̺ is unknown.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Stochastic Processes and their Applications
سال: 1979
ISSN: 0304-4149
DOI: 10.1016/0304-4149(79)90034-6