Markov Decision Processes

Discrete Stochastic Dynamic Programming

M.L. Puterman (Autor)

Buch | Hardcover

672 Seiten

1994
John Wiley & Sons Inc (Verlag)
978-0-471-61977-2 (ISBN)

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A Markov chain is a sequence of events where the probability of each event is dependent on the event immediately preceding it, but independent of earlier events. Models and numerical equations are used to describe the patterns. This process is particularly useful in operations research and decision science for plotting the sequence of actions which will cause a system to perform optimally. This study provides a unified treatment of the theory, applications and computational methods for Markov decision processes. Important topics featured include action elimination methods, value iteration in the average reward case and sensitive discount optimality.

Model Formulation. Examples. Finite--Horizon Markov Decision Processes. Infinite--Horizon Models: Foundations. Discounted Markov Decision Problems. The Expected Total--Reward Criterion. Average Reward and Related Criteria. The Average Reward Criterion--Multichain and Communicating Models. Sensitive Discount Optimality. Continuous--Time Models. Afterword. Notation. Appendices. Bibliography. Index.

Erscheint lt. Verlag	23.5.1994
Reihe/Serie	Wiley Series in Probability & Mathematical Statistics: Applied Probability & Statistics
Verlagsort	New York
Sprache	englisch
Maße	162 x 242 mm
Gewicht	1049 g
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
ISBN-10	0-471-61977-9 / 0471619779
ISBN-13	978-0-471-61977-2 / 9780471619772
Zustand	Neuware