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Markov Decision Processes In Artificial Intelligence Olivier Sigaud

  • SKU: BELL-4307686
Markov Decision Processes In Artificial Intelligence Olivier Sigaud
$ 31.00 $ 45.00 (-31%)

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Markov Decision Processes In Artificial Intelligence Olivier Sigaud instant download after payment.

Publisher: Wiley-ISTE
File Extension: PDF
File size: 19.1 MB
Pages: 466
Author: Olivier Sigaud, Olivier Buffet
ISBN: 9781118557426, 9781848211674, 1118557425, 1848211678
Language: English
Year: 2010

Product desciption

Markov Decision Processes In Artificial Intelligence Olivier Sigaud by Olivier Sigaud, Olivier Buffet 9781118557426, 9781848211674, 1118557425, 1848211678 instant download after payment.

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.Content:
Chapter 1 Markov Decision Processes (pages 1–38): Frederick Garcia and Emmanuel Rachelson
Chapter 2 Reinforcement Learning (pages 39–66): Olivier Sigaud and Frederick Garcia
Chapter 3 Approximate Dynamic Programming (pages 67–98): Remi Munos
Chapter 4 Factored Markov Decision Processes (pages 99–126): Thomas Degris and Olivier Sigaud
Chapter 5 Policy?Gradient Algorithms (pages 127–152): Olivier Buffet
Chapter 6 Online Resolution Techniques (pages 153–184): Laurent Peret and Frederick Garcia
Chapter 7 Partially Observable Markov Decision Processes (pages 185–228): Alain Dutech and Bruno Scherrer
Chapter 8 Stochastic Games (pages 229–276): Andriy Burkov, Laetitia Matignon and Brahim Chaib?Draa
Chapter 9 DEC?MDP/POMDP (pages 277–318): Aurelie Beynier, Francois Charpillet, Daniel Szer and Abdel?Illah Mouaddib
Chapter 10 Non?Standard Criteria (pages 319–360): Matthieu Boussard, Maroua Bouzid, Abdel?Illah Mouaddib, Regis Sabbadin and Paul Weng
Chapter 11 Online Learning for Micro?Object Manipulation (pages 361–374): Guillaume Laurent
Chapter 12 Conservation of Biodiversity (pages 375–394): Iadine Chades
Chapter 13 Autonomous Helicopter Searching for a Landing Area in an Uncertain Environment (pages 395–412): Patrick Fabiani and Florent Teichteil?Kunigsbuch
Chapter 14 Resource Consumption Control for an Autonomous Robot (pages 413–424): Simon Le Gloannec and Abdel?Illah Mouaddib
Chapter 15 Operations Planning (pages 425–452): Sylvie Thiebaux and Olivier Buffet

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