Publicación: Maximizing the probability of visiting a set infinitely often for a countable state space Markov decision process
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2022-01-15
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info:eu-repo/semantics/openAccess
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Elsevier
Resumen
We consider a Markov decision process with countable state space and Borel action space. We are interested in maximizing the probability that the controlled Markov chain visits some subset of the state space infinitely often. We provide sufficient conditions, based on continuity and compactness requirements, together with a stability condition on a parametrized family of auxiliary control models, which imply the existence of an optimal policy that is deterministic and stationary.
We compare our hypotheses with those existing in the literature.
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Categorías UNESCO
Palabras clave
Markov decision process, countable state space, visiting a set in- finitely often, non-additive optimality criterion
Citación
François Dufour, Tomás Prieto-Rumeau, Maximizing the probability of visiting a set infinitely often for a countable state space Markov decision process, Journal of Mathematical Analysis and Applications, Volume 505, Issue 2, paper 125639 (2022). https://www.sciencedirect.com/science/article/abs/pii/S0022247X21007186 https://doi.org/10.1016/j.jmaa.2021.125639
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Facultades y escuelas::Facultad de Ciencias
Departamento
Estadística, Investigación Operativa y Cálculo Numérico