Andrew G. Barto

Andrew G. Barto

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Andrew Barto is Professor Emeritus in the College of Information and Computer Sciences at University of Massachusetts Amherst. He is a Co-Director at Autonomous Learning Laboratory. His research interests are theory and application of methods for learning and planning in stochastic sequential decision problems; algebraic approaches to abstraction; psychology, neuroscience, and computational theory of motivation, reward, and addiction; computational models of learning and adaptation in animal motor control systems. 

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Books Authored by Andrew G. Barto

Reinforcement Learning: An Introduction, Second Edition (Draft)

Post date: 09 Jan 2017
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.
Author(s): Andrew G. Barto Richard S. Sutton
Publication date: 30 Sep 2016
Document Type: Textbook
Tags: Machine Learning
 
Reinforcement Learning: An Introduction, Second Edition (Draft)

Reinforcement Learning: An Introduction, Second Edition (Draft)

Post date: 09 Jan 2017
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.
Author(s): Andrew G. Barto Richard S. Sutton
Publication date: 30 Sep 2016
Document Type: Textbook
Tags: Machine Learning


Reinforcement Learning: An Introduction

Post date: 04 Oct 2007
Provides a clear and simple account of the key ideas and algorithms of reinforcement learning. Familiarity with elementary concepts of probability is assumed.
 
Reinforcement Learning: An Introduction

Reinforcement Learning: An Introduction

Post date: 04 Oct 2007
Provides a clear and simple account of the key ideas and algorithms of reinforcement learning. Familiarity with elementary concepts of probability is assumed.


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