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Persistent link: https://www.econbiz.de/10003974003
In this paper we study Markov Decision Process (MDP) problems with the restriction that at decision epochs only a finite number of given Markovian decision rules may be applied. The elements of the finite set of allowed decision rules should be mixed to improve the performance. The set of...
Persistent link: https://www.econbiz.de/10011380145
Persistent link: https://www.econbiz.de/10003155798
This paper provides series expansions of the stationary distribution of a finite Markov chain. This leads to an efficient numerical algorithm for computing the stationary distribution of a finite Markov chain. Numerical examples are given to illustrate the performance of the algorithm.
Persistent link: https://www.econbiz.de/10011346475
Persistent link: https://www.econbiz.de/10001415240
This paper provides series expansions of the stationary distribution of a finite Markov chain. This leads to an efficient numerical algorithm for computing the stationary distribution of a finite Markov chain. Numerical examples are given to illustrate the performance of the algorithm
Persistent link: https://www.econbiz.de/10014027524
In this paper we study Markov Decision Process (MDP) problems with the restriction that at decision epochs only a finite number of given Markovian decision rules may be applied. The elements of the finite set of allowed decision rules should be mixed to improve the performance. The set of...
Persistent link: https://www.econbiz.de/10013146330