Maximizing the set of recurrent states of an MDP subject to convex constraints super()

This paper focuses on the design of time-homogeneous fully observed Markov decision processes (MDPs), with finite state and action spaces. The main objective is to obtain policies that generate the maximal set of recurrent states, subject to convex constraints on the set of invariant probability mas...

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Veröffentlicht in:	Automatica (Oxford) 2014-03, Vol.50 (3), p.994-998
Hauptverfasser:	Arvelo, Eduardo, Martins, Nuno C
Format:	Artikel
Sprache:	eng
Schlagworte:	Automation Entropy Invariants Markov processes Mathematical analysis Mathematical models Maximization Policies
Online-Zugang:	Volltext
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