Markov Decision Processes in Artificial Intelligence

Download or Read eBook Markov Decision Processes in Artificial Intelligence PDF written by Olivier Sigaud and published by John Wiley & Sons. This book was released on 2013-03-04 with total page 367 pages. Available in PDF, EPUB and Kindle.
Markov Decision Processes in Artificial Intelligence
Author :
Publisher : John Wiley & Sons
Total Pages : 367
Release :
ISBN-10 : 9781118620106
ISBN-13 : 1118620100
Rating : 4/5 (06 Downloads)

Book Synopsis Markov Decision Processes in Artificial Intelligence by : Olivier Sigaud

Book excerpt: 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.


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