Markov Decision Processes: Discrete Stochastic Dynamic Programming (Wiley Series in Probability and Statistics)
A comprehensive treatment of Markov decision processes and discrete stochastic dynamic programming, covering theory, algorithms, and applications in probability and statistics.
About This Book
This book presents the theory and methods of Markov decision processes for discrete stochastic dynamic programming.
It covers finite and infinite horizon problems, policy iteration, value iteration, and related computational techniques.
The text is part of the Wiley Series in Probability and Statistics and serves as a reference for researchers and practitioners.
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