Results 141 to 150 of about 9,481,834 (176)

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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Optimization for condition-based maintenance with semi-Markov decision process

Reliability Engineering & System Safety, 2005
The semi-Markov decision model is a powerful tool in analyzing sequential decision processes with random decision epochs. In this paper, we have built the semi-Markov decision process (SMDP) for the maintenance policy optimization of condition-based preventive maintenance problems, and have presented the approach for joint optimization of inspection ...
Dongyan Chen, Kishor S. Trivedi
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Performance Optimization of Semi-Markov Decision Processes with Discounted-cost Criteria

European Journal of Control, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baoqun Yin, Yanjie Li, Yaping Zhou, Hongsheng Xi   +3 more
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Semi-Markov decision processes with polynomial reward

Journal of Applied Probability, 1982
A semi-Markov decision process, with a denumerable multidimensional state space, is considered. At any given state only a finite number of actions can be taken to control the process. The immediate reward earned in one transition period is merely assumed to be bounded by a polynomial and a bound is imposed on a weighted moment of the next state reached
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Average Reward Reinforcement Learning for Semi-Markov Decision Processes

2017
In this paper, we study new reinforcement learning (RL) algorithms for Semi-Markov decision processes (SMDPs) with an average reward criterion. Based on the discrete-time type Bellman optimality equation, we use incremental value iteration (IVI), stochastic shortest path (SSP) value iteration and bisection algorithms to derive novel RL algorithms in a ...
Jiayuan Yang, Yanjie Li, Haoyao Chen, Jiangang Li   +3 more
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Reinforcement learning for semi-Markov decision processes with applications

2023
This thesis focuses on semi-Markov decision processes and their connection with Reinforcement Learning via Q-learning technique. We start by discussing some general ideas around Machine Learning, Reinforcement Learning and Hierarchical Reinforcement Learning.
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Constrained Discounted Semi-Markov Decision Processes

2002
This paper reduces problems on the existence and the finding of optimal policies for multiple criterion discounted SMDPs to similar problems for MDPs. We prove this reduction and illustrate it by extending to SMDPs several results for constrained discounted MDPs.
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