Results 251 to 260 of about 14,317,493 (293)

Cost rate heuristics for semi-Markov decision processes

Journal of Applied Probability, 1992
In response to the computational complexity of the dynamic programming/backwards induction approach to the development of optimal policies for semi-Markov decision processes, we propose a class of heuristics resulting from an inductive process which proceeds forwards in time.
Glazebrook, K.D., Bailey, Michael P., Whitaker, Lyn R.   +2 more
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Constrained Semi-Markov decision processes with average rewards

ZOR Zeitschrift f�r Operations Research Mathematical Methods of Opeartions Research, 1994
This paper deals with constrained average reward semi-Markov decision processes with finite state and action sets. Two average reward criteria are considered, namely time average and ratio average. The author proved the existence of optimal mixed stationary policies and showed, under the unichain condition, the existence of randomized stationary ...
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Denumerable Undiscounted Semi-Markov Decision Processes with Unbounded Rewards

Mathematics of Operations Research, 1983
This paper establishes the existence of a solution to the optimality equations in undis-counted 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 ...
Awi Federgruen, Paul J. Schweitzer, Henk C. Tijms   +2 more
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Generalized semi-Markov decision processes

Journal of Applied Probability, 1979
Various authors have derived the necessary and sufficient conditions for optimality in semi-Markov decision processes in which the state remains constant between jumps. In this paper similar results are presented for a generalized semi-Markov decision process in which the state varies between jumps according to a Markov process with continuous sample ...
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Inspection and maintenance planning: an application of semi-Markov decision processes

Journal of Intelligent Manufacturing, 1997
In this paper, we consider a system which deteriorates stochastically from one time unit to another. The state of the system, which is a continuous random variable, can be observed only by inspection. The goal of this paper is to derive a predictive maintenance policy which indicates, at each inspection and according to the observed value, whether a ...
Bérenguer, Christophe, Chu, Chengbin, Grall, Antoine   +2 more
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On undiscounted semi-Markov decision processes with absorbing states

Mathematical Methods of Operations Research, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Optimum maintenance policy using semi-Markov decision processes

Electric Power Systems Research, 2006
A method is presented to solve for the optimum maintenance policy of repairable power equipment. The approach uses a continuous-time semi-Markov process (SMP) to first find the optimal maintenance rate for maximum availability of the equipment. Then a semi-Markov decision process (SMDP) is utilized to determine whether maintenance should be performed ...
Curtis L. Tomasevicz, Sohrab Asgarpoor
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Error bounds of optimization algorithms for semi-Markov decision processes

International Journal of Systems Science, 2007
Cao's work shows that, by defining an α-dependent equivalent infinitesimal generator Aα, a semi-Markov decision process (SMDP) with both average- and discounted-cost criteria can be treated as an α-equivalent Markov decision process (MDP), and the performance potential theory can also be developed for SMDPs. In this work, we focus on establishing error
Tang Hao, Baoqun Yin, Hongsheng Xi
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Optimal threshold probability and expectation in semi-Markov decision processes

Applied Mathematics and Computation, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Masahiko Sakaguchi, Yoshio Ohtsubo
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An inverse reinforcement learning algorithm for semi-Markov decision processes

2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2017
In this paper, we study the inverse reinforcement learning (IRL) algorithm for semi-Markov decision processes (SMDPs) with average reward based on the performance sensitivity analysis. By analyzing the structural form of the performance difference formula between any two different policies, we utilize the expert policy to transform the IRL problems of ...
Chuanfang Tan, Yanjie Li, Yuhu Cheng
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