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Dynamic programming and stochastic control by Dimitri P. Bertsekas

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Published by Academic Press in New York .
Written in English


  • Dynamic programming.,
  • Stochastic control theory.

Book details:

Edition Notes

StatementDimitri P. Bertsekas.
SeriesMathematics in science and engineering ;, v. 125
LC ClassificationsT57.83 .B48
The Physical Object
Paginationxv, 397 p. :
Number of Pages397
ID Numbers
Open LibraryOL4885918M
ISBN 100120932504
LC Control Number76016143

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Markov Decision Processes: Discrete Stochastic Dynamic Programming represents an up-to-date, unified, and rigorous treatment of theoretical and computational aspects of discrete-time Markov decision processes." ―Journal of the American Statistical AssociationCited by: Originally introduced by Richard E. Bellman in (Bellman ), stochastic dynamic programming is a technique for modelling and solving problems of decision making under larep-immo.comy related to stochastic programming and dynamic programming, stochastic dynamic programming represents the problem under scrutiny in the form of a Bellman equation. Click here to download lecture slides for the MIT course "Dynamic Programming and Stochastic Control (), Dec. The last six lectures cover a lot of the approximate dynamic programming material. Click here to download research papers and other material on Dynamic Programming and Approximate Dynamic Programming. The main topic of this book is optimization problems involving uncertain parameters, for which stochastic models are available. Although many ways have been proposed to model uncertain quantities, stochastic models have proved their flexibility and usefulness in diverse areas of science. This is mainly due to solid mathematical foundations and.

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