Markov Decision Processes in Artificial Intelligence

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Markov Decision Processes in Artificial Intelligence is written by Olivier Sigaud and published by John Wiley & Sons. It's available with International Standard Book Number or ISBN identification 1118620100 (ISBN 10) and 9781118620106 (ISBN 13).

Markov Decision Processes (MDPs) are a mathematical framework for modeling sequential decision problems under uncertainty as well as reinforcement learning problems. Written by experts in the field, this book provides a global view of current research using MDPs in artificial intelligence. It starts with an introductory presentation of the fundamental aspects of MDPs (planning in MDPs, reinforcement learning, partially observable MDPs, Markov games and the use of non-classical criteria). It then presents more advanced research trends in the field and gives some concrete examples using illustrative real life applications.