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Simulation-based Algorithms for Markov Decision Processes
Langbeschreibung
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. It is well-known that many real-world problems modeled by MDPs have huge state and/or action spaces, leading to the notorious curse of dimensionality that makes practical solution of the resulting models intractable. In other cases, the system of interest is complex enough that it is not feasible to specify some of the MDP model parameters explicitly, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based numerical algorithms have been developed recently to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function. Specific approaches include:
Hauptbeschreibung
"Often, real-world problems modeled by Markov decision processes (MDPs) are difficult to solve in practise because of the curse of dimensionality. In others, explicit specification of the MDP model parameters is not feasible, but simulation samples are available. For these settings, various sampling and population-based numerical algorithms for computing an optimal solution in terms of a policy and/or value function have been developed recently.
Inhaltsverzeichnis
Markov Decision Processes.- Multi-stage Adaptive Sampling Algorithms.- Population-based Evolutionary Approaches.- Model Reference Adaptive Search.- On-line Control Methods via Simulation.
Steven I. Marcus received his Ph.D. and S.M. from the Massachusetts Institute of Technology in 1975 and 1972, respectively. He received a B.A. from Rice University in 1971. From 1975 to 1991, he was with the Department of Electrical and Computer Engineering at the University of Texas at Austin, where he was the L.B. (Preach) Meaders Professor in Engineering. He was Associate Chairman of the Department during the period 1984-89. In 1991, he joined the University of Maryland, College Park, where he was Director of the Institute for Systems Research until 1996. He is currently a Professor in the Electrical Engineering Department and the Institute for Systems Research.
ISBN-13:
9781846286902
Veröffentl:
2007
Seiten:
189
Autor:
Hyeong Soo Chang
Serie:
Communications and Control Engineering
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
1 - PDF Watermark
Sprache:
Englisch
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