Markov Decision Processes and Reinforcement Learning
by Martin L. Puterman, Timothy C. Y. Chan
Markov Decision Processes and Reinforcement Learning offers a focused academic examination of two important areas in sequential decision-making. Written by Martin L. Puterman and Timothy C. Y. Chan, this resource is intended for readers studying the mathematical and computational foundations of these related subjects.
About This Book
Markov Decision Processes and Reinforcement Learning examines two closely related areas central to sequential decision-making.
The book focuses on Markov decision processes and reinforcement learning, as indicated by its title.
Written by Martin L. Puterman and Timothy C. Y. Chan, it is suited to readers seeking a focused academic treatment of these subjects.
Its subject matter connects mathematical decision models with learning-based approaches to making choices over time.
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