Markov Decision Processes in Artificial Intelligence (repost)
Markov Decision Processes in Artificial Intelligence by Olivier Sigaud and Olivier Buffet
English | ISBN: 1848211678 | 2010 | 480 pages | PDF | 19 MB
English | ISBN: 1848211678 | 2010 | 480 pages | PDF | 19 MB
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). Then it presents more advanced research trends in the domain and gives some concrete examples using illustrative applications.