Technical Reinforcement Learning: An Introduction (0262193981)

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Reinforcement learning is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In this book, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.

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	Study Recent Advances in Reinforcement Learning Recent Advances in Reinforcement Learning: 8th European Workshop, EWRL 2008, Villeneuve d'Ascq, France, June 30-July 3, 2008283 pages \| Springer; 1 edition (December 1, 2008) \| ISBN-10: 3540897216 \| PDF \| 10 MbThis book constitutes revised ...
	Science/Engineering Transfer in Reinforcement Learning Domains Transfer in Reinforcement Learning Domains (Studies in Computational Intelligence) by Matthew E. TaylorPublisher: Springer \| Number Of Pages: 235 \| Publication Date: 2009-08-01 \| ISBN-10: 3642018815 \| PDF \| 2 MbIn reinforcement learni ...
	Study Motivated Reinforcement Learning: Curious Characters for Multiuser Games Motivated Reinforcement Learning: Curious Characters for Multiuser GamesSpringer \| ISBN: 3540891862 \| 2009-07-01 \| PDF \| 206 pages \| 9 Mb Motivated learning is an emerging research field in artificial intelligence and cognitive modelling. C ...
	Science/Engineering Adaptive Brain: Cognition, Learning, Reinforcement and Rhythm Pt. 1 by Stephen Grossberg Adaptive Brain: Cognition, Learning, Reinforcement and Rhythm Pt. 1 by Stephen GrossbergPublisher: Elsevier Science \| December 1986 \| ISBN: 0444701176 \| Pages: 518 \| PDF \| 9.3 MBThese books bring together recent neural models of vision, spe ...
	Technical Reinforcement Learning The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too com ...
	Programming Reinforcement Learning: Theory and Applications Cornelius Weber, Mark Elshaw and Norbert Michael Mayer “Reinforcement Learning: Theory and Applications" I-Tech Education and Publishing, Vienna, Austria \| 2008-01 \| ISBN: 9783902613141 \| 424 pages \| PDF \| 11,7 MB Brains rule the world ...

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	Study Recent Advances in Reinforcement Learning Recent Advances in Reinforcement Learning: 8th European Workshop, EWRL 2008, Villeneuve d'Ascq, France, June 30-July 3, 2008283 pages \| Springer; 1 edition (December 1, 2008) \| ISBN-10: 3540897216 \| PDF \| 10 MbThis book constitutes revised ...
	Science/Engineering Transfer in Reinforcement Learning Domains Transfer in Reinforcement Learning Domains (Studies in Computational Intelligence) by Matthew E. TaylorPublisher: Springer \| Number Of Pages: 235 \| Publication Date: 2009-08-01 \| ISBN-10: 3642018815 \| PDF \| 2 MbIn reinforcement learni ...
	Study Motivated Reinforcement Learning: Curious Characters for Multiuser Games Motivated Reinforcement Learning: Curious Characters for Multiuser GamesSpringer \| ISBN: 3540891862 \| 2009-07-01 \| PDF \| 206 pages \| 9 Mb Motivated learning is an emerging research field in artificial intelligence and cognitive modelling. C ...
	Science/Engineering Adaptive Brain: Cognition, Learning, Reinforcement and Rhythm Pt. 1 by Stephen Grossberg Adaptive Brain: Cognition, Learning, Reinforcement and Rhythm Pt. 1 by Stephen GrossbergPublisher: Elsevier Science \| December 1986 \| ISBN: 0444701176 \| Pages: 518 \| PDF \| 9.3 MBThese books bring together recent neural models of vision, spe ...
	Technical Reinforcement Learning The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too com ...
	Programming Reinforcement Learning: Theory and Applications Cornelius Weber, Mark Elshaw and Norbert Michael Mayer “Reinforcement Learning: Theory and Applications" I-Tech Education and Publishing, Vienna, Austria \| 2008-01 \| ISBN: 9783902613141 \| 424 pages \| PDF \| 11,7 MB Brains rule the world ...

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