Constrained Continuous-Time Markov Decision Processes on the Finite Horizon

Constrained Continuous-Time Markov Decision Processes on the Finite Horizon This paper studies the constrained (nonhomogeneous) continuous-time Markov decision processes on the finite horizon. The performance criterion to be optimized is the expected total reward on the finite horizon, while N constraints are imposed on similar expected costs. Introducing the appropriate notion of the occupation measures for the concerned optimal control problem, we establish the following under some suitable conditions: (a) the class of Markov policies is sufficient; (b) every extreme point of the space of performance vectors is generated by a deterministic Markov policy; and (c) there exists an optimal Markov policy, which is a mixture of no more than $$N+1$$ N + 1 deterministic Markov policies. Applied Mathematics and Optimization Springer Journals

Constrained Continuous-Time Markov Decision Processes on the Finite Horizon

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Springer US
Copyright © 2016 by Springer Science+Business Media New York
Mathematics; Calculus of Variations and Optimal Control; Optimization; Systems Theory, Control; Theoretical, Mathematical and Computational Physics; Mathematical Methods in Physics; Numerical and Computational Physics, Simulation
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