Learning Reinforcement Theory
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Learning Reinforcement Theory
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Author : Fred Simmons Keller
language : en
Publisher:
Release Date : 1969
Learning Reinforcement Theory written by Fred Simmons Keller and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1969 with Educational psychology categories.
Learning
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Author : Fred Simmons Keller
language : en
Publisher: Random House Incorporated
Release Date : 1969-06
Learning written by Fred Simmons Keller and has been published by Random House Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1969-06 with Education categories.
The Nature Of Reinforcement
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Author : University of Pittsburgh. Learning Research and Development Center
language : en
Publisher:
Release Date : 1971
The Nature Of Reinforcement written by University of Pittsburgh. Learning Research and Development Center and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1971 with Psychology categories.
Learning And Its Effect
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Author : Hiriyappa B
language : en
Publisher: Lulu.com
Release Date : 2010-12-08
Learning And Its Effect written by Hiriyappa B and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-12-08 with Education categories.
This books deals with the Definitions of learning, Component of learning, Determinants of learning, Learning process, Principles of learning, Reinforcement, Types of reinforcement, Schedules of reinforcement, Kinds of partial reinforcement schedule, Comparisons of schedules of reinforcement, Contingency of reinforcement, Types of contingencies of reinforcement, Punishment , How to make punishment effective, Guidelines for using effective punishment, Potential negative effects of punishment, Reinforcement strategies, Organizational reward system, Types of rewards, Extrinsic rewards, Financial rewards / monetary rewards, Performance based financial or monetary rewards, Membership based financial or monetary rewards, Non financial rewards / non monetary rewards, Rewards used by organizations, Types of learning, Learning theories, Classical conditioning theory, Operant conditioning theory, Difference between classical conditioning and operant conditioning, Cognitive learning theory and Social learning theory
About Learning
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Author : Louis Everstine
language : en
Publisher: Xlibris Corporation
Release Date : 2014-10-06
About Learning written by Louis Everstine and has been published by Xlibris Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-06 with Psychology categories.
This book traces the development of learning theory in Psychology. Each major theory of the past century is analyzed in detail, and in terms of its evolution from those that preceded it. Theory-building is cumulative, each new idea standing on the shoulders of earlier ones, according to the logical progression of thesis to antithesis to synthesis. On what we learned from the subject of this book, learning, we learned from what was learned before. A classical example of theory developing by trial and error, fits and starts, blind alleys and flashes of insight is the discovery of the DNA molecule. At least three laboratories, in England and America, were closing-in on the answer at the same time, competing with each-other as they reached the finish-line. Each following its governing theory--for instance, Linus Pauling’s gamble on a triple helix--the lads from Cambridge won the race, and the rest, as they say, is History. None of the drama of that campaign to find the truth of a natural phenomenon is to be found here, with one exception: the gradual process of one theory morphing into another, on the strength of a new idea, has finally yielded a workable synthesis of how we learn. This result is presented here in precise, simple terms that leave jargon behind. A totally new theory of human learning is presented here. Three basic principles are put forward: Promising, Demonstrating, and Commanding. Methods are provided for their implementation.
Foundations Of Deep Reinforcement Learning
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Author : Laura Graesser
language : en
Publisher: Addison-Wesley Professional
Release Date : 2019-11-20
Foundations Of Deep Reinforcement Learning written by Laura Graesser and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-20 with Computers categories.
The Contemporary Introduction to Deep Reinforcement Learning that Combines Theory and Practice Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games—such as Go, Atari games, and DotA 2—to robotics. Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problem Explore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER) Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO) Understand how algorithms can be parallelized synchronously and asynchronously Run algorithms in SLM Lab and learn the practical implementation details for getting deep RL to work Explore algorithm benchmark results with tuned hyperparameters Understand how deep RL environments are designed Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Learning Theory And Behavior
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Author : Orval Hobart Mowrer
language : en
Publisher:
Release Date : 1960
Learning Theory And Behavior written by Orval Hobart Mowrer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1960 with Behaviorism (Psychology). categories.
Introduction: historical review and perspective; The law of effect, conditioning, and the problem of punishment; Two factor learning theory: versions one and two; Two conceptions of secondary reinforcement; Secondary reinforcement: a unifying theory; Secondary reinforcement: reservations and complications; Revised two factor theory and the concept of habit; Other theories, and some further evidence, compared; Hope, fear, and field theory; Gradients of reinforcement (type-D and type-I) and temporal integration, Unlearning, conflict, frustration, and courage; Generalization, discrimination, and skill.
The Power Of Reinforcement
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Author : Stephen Ray Flora
language : en
Publisher: State University of New York Press
Release Date : 2012-02-01
The Power Of Reinforcement written by Stephen Ray Flora and has been published by State University of New York Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-01 with Social Science categories.
2004 CHOICE Outstanding Academic Title According to Stephen Ray Flora, reinforcement is a very powerful tool for improving the human condition despite often being dismissed as regarding people as less than human and as "overly simplistic." This book addresses and defends the use of reinforcement principles against a wide variety of attacks. Countering the myths, criticisms, and misrepresentations of reinforcement, including false claims that reinforcement is "rat psychology," the author shows that building reinforcement theory on basic laboratory research is a strength, not a weakness, and allows unlimited applications to human situations as it promotes well-being and productivity. Also examined are reinforcement contingencies, planned or accidental, as they shape behavioral patterns and repertoires in a positive way.
Response
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Author : Louis Everstine
language : en
Publisher: Xlibris Corporation
Release Date : 2011-09-30
Response written by Louis Everstine and has been published by Xlibris Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-30 with Psychology categories.
This book traces the development of learning theory in Psychology. Each major theory of the past century is analyzed in detail, and in terms of its evolution from those that preceded it. Theory-building is cumulative, each new idea standing on the shoulders of earlier ones, according to the logical progression of thesis to antithesis to synthesis. On what we learned from the subject of this book, learning, we learned from what was learned before. A classical example of theory developing by trial and error, fits and starts, blind alleys and flashes of insight is the discovery of the DNA molecule. At least three laboratories, in England and America, were closing-in on the answer at the same time, competing with each-other as they reached the finish-line. Each following its governing theory--for instance, Linus Pauling's gamble on a triple helix--the lads from Cambridge won the race, and the rest, as they say, is History. None of the drama of that campaign to find the truth of a natural phenomenon is to be found here, with one exception: the gradual process of one theory morphing into another, on the strength of a new idea, has finally yielded a workable synthesis of how we learn. This result is presented here in precise, simple terms that leave jargon behind.
Reinforcement Learning Second Edition
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Author : Richard S. Sutton
language : en
Publisher: MIT Press
Release Date : 2018-11-13
Reinforcement Learning Second Edition written by Richard S. Sutton and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-13 with Computers categories.
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.