Exact decomposition approaches for Markov decision processes: a survey.
Daoui, Cherki, Abbad, Mohamed, Tkiouat, Mohamed (2010)
Advances in Operations Research
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Displaying similar documents to “Dynamic system evolution and Markov chain approximation.”
Exact decomposition approaches for Markov decision processes: a survey.
A theoretical analysis of season length restrictions in fisheries management.
Xu, Qing, Batabyal, Amitrajeet A. (2002)
Discrete Dynamics in Nature and Society
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A stochastic cobweb dynamical model.
Brianzoni, Serena, Mammana, Cristiana, Michetti, Elisabetta, Zirilli, Francesco (2008)
Discrete Dynamics in Nature and Society
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A mathematical framework for learning and adaption: (generalized) random systems with complete connections.
Ulrich Herkenrath, Radu Theodorescu (1981)
Trabajos de Estadística e Investigación Operativa
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The aim of this paper is to show that the theory of (generalized) random systems with complete connection may serve as a mathematical framework for learning and adaption. Chapter 1 is of an introductory nature and gives a general description of the problems with which one is faced. In Chapter 2 the mathematical model and some results about it are explained. Chapter 3 deals with special learning and adaption models.
Fast simulation for road traffic network
Roberta Jungblut-Hessel, Brigitte Plateau, William J. Stewart, Bernard Ycart (2001)
RAIRO - Operations Research - Recherche Opérationnelle
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In this paper we present a method to perform fast simulation of large markovian systems. This method is based on the use of three concepts: Markov chain uniformization, event-driven dynamics, and modularity. An application of urban traffic simulation is presented to illustrate the performance of our approach.
Time-discretization for controlled Markov processes. I. General approximation results
Nico M. van Dijk, Arie Hordijk (1996)
Kybernetika
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Limit theorems for discrete-time metapopulation models.
Buckley, F.M., Pollett, P.K. (2010)
Probability Surveys [electronic only]
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Option pricing in a regime-switching model using the fast Fourier transform.
Liu, R.H., Zhang, Q., Yin, G. (2006)
Journal of Applied Mathematics and Stochastic Analysis
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Estimates for perturbations of average Markov decision processes with a minimal state and upper bounded by stochastically ordered Markov chains
Raúl Montes-de-Oca, Francisco Salem-Silva (2005)
Kybernetika
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This paper deals with Markov decision processes (MDPs) with real state space for which its minimum is attained, and that are upper bounded by (uncontrolled) stochastically ordered (SO) Markov chains. We consider MDPs with (possibly) unbounded costs, and to evaluate the quality of each policy, we use the objective function known as the average cost. For this objective function we consider two Markov control models and . and have the same components except for the transition laws....