Results 151 to 160 of about 81,989 (164)

Performance Optimization of Semi-Markov Decision Processes with Discounted-cost Criteria

European Journal of Control, 2008
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Yin, Baoqun, Li, Yanjie, Zhou, Yaping, Xi, Hongsheng   +3 more
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Finite horizon semi-Markov decision processes with multiple constraints

Proceeding of the 11th World Congress on Intelligent Control and Automation, 2014
This paper focuses on solving a finite horizon semi-Markov decision process with multiple constraints. We convert the problem to a constrained absorbing discrete-time Markov decision process and then to an equivalent linear programm over a class of occupancy measures.
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Learning Automaton for Finite Semi-Markov Decision Processes

1983
A finite semi-Markov decision process is studied to maximize the expected average reward. The semi-Markov kernel of the process depends on an unknown parameter taking values in a subset [a, b] of ℝS. A controller modelled as a learning automaton updates sequentially the probabilities of generating decisions based on the observed decisions, states, and ...
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Semi-Markov decision processes with a reachable state-subset

Optimization, 1989
We consider the problem of minimizing the long-run average expected cost per unit time in a semi-Markov decision process with arbitrary state and action space, Assuming the existence .of a Borel subset of state space called a reachable state-subset, we derive the optimality equation for the unbounded costs.
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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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On undiscounted semi-Markov decision processes with absorbing states

Mathematical Methods of Operations Research, 2015
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Reinforcement learning with options in semi Markov decision processes

2021
Treball fi de màster de: Master in Intelligent Interactive ...
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Semi-Markov Decision-Making Processes with Vector Gains

Theory of Probability & Its Applications, 1984
Vinogradskaya, T. M., Geninson, B. A., Rubchinskij, A. A.   +2 more
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Deterministic policy gradient algorithms for semi‐Markov decision processes

International Journal of Intelligent Systems, 2021
Ashkan Haji Hosseinloo, Munther A. Dahleh   +1 more
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On the Optimality Conditions for Semi-Markov Decision Processes

1977
The paper presents a recurrence formula for the difference between expected rewards and sojourn times generated by N transitions of a semi-Markov decision process with finite state space. Using the recurrence formula convergence of policy iteration method can be easily verified and also necessary and sufficient optimality conditions for average optimal
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