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Category :
Languages : en
Pages : 216
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Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 216
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ISBN:
Category :
Languages : en
Pages : 44
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Author: Joseph E. DiGenova
Publisher:
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Category : Government publications
Languages : en
Pages : 422
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Book Description
Author: Kent Beck
Publisher: Pearson Education
ISBN: 0321278658
Category : Computers
Languages : en
Pages : 218
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Book Description
Accountability. Transparency. Responsibility. These are not words that are often applied to software development. In this completely revised introduction to Extreme Programming (XP), Kent Beck describes how to improve your software development by integrating these highly desirable concepts into your daily development process. The first edition of Extreme Programming Explained is a classic. It won awards for its then-radical ideas for improving small-team development, such as having developers write automated tests for their own code and having the whole team plan weekly. Much has changed in five years. This completely rewritten second edition expands the scope of XP to teams of any size by suggesting a program of continuous improvement based on.
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Category : Legal briefs
Languages : en
Pages : 524
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Author:
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Category : Electronic journals
Languages : en
Pages : 656
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Book Description
1947-1951 volumes contain fifth issue: Survey of New York Law.
Author: Harold Remington
Publisher:
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Category : Bankruptcy
Languages : en
Pages : 772
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Author: United States
Publisher:
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Category : Law
Languages : en
Pages : 588
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Author:
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Category : Courts
Languages : en
Pages : 1180
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Book Description
Author: Richard S. Sutton
Publisher: MIT Press
ISBN: 0262352702
Category : Computers
Languages : en
Pages : 549
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Book Description
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
