Andrew Barto

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Andrew G. Barto, an American computer scientist, AI-researcher and Professor of Computer Science, University of Massachusetts, Amherst. His research centers on learning in natural and artificial systems, and he has studied machine learning algorithms since 1977, contributing to the development of the computational theory and practice of reinforcement learning.

=Selected Publications=

1980 ...

 * Richard Sutton, Andrew Barto (1981). Toward a modern theory of adaptive networks: Expectation and prediction. Psychological Review, Vol. 88, pdf
 * Andrew Barto, Richard Sutton, Christopher J. C. H. Watkins (1989). Sequential Decision Problems and Neural Networks. NIPS 1989

1990 ...

 * Richard Sutton, Andrew Barto (1990). Time-Derivative Models of Pavlovian Reinforcement. in Michael Gabriel, John Moore (eds.) (1990). Learning and Computational Neuroscience: Foundations of Adaptive Networks. MIT Press
 * Richard C. Yee, Sharad Saxena, Paul E. Utgoff, Andrew Barto (1990). Explaining Temporal Differences to Create Useful Concepts for Evaluating States. AAAI 1990, pdf
 * Steven Bradtke, Andrew Barto (1996) Linear Least-Squares Algorithms for Temporal Difference Learning. Machine Learning, Vol. 22, Nos. 1/2/3, pdf
 * Richard Sutton, Andrew Barto (1998). Reinforcement Learning: An Introduction. MIT Press

2000 ...

 * Andrew Barto (2007). Temporal difference learning. Scholarpedia 2(11):1604

2010 ...

 * Andrew Barto (2010). Adaptive Real-Time Dynamic Programming. Encyclopedia of Machine Learning 2010, Springer
 * Andrew Barto (2017). Adaptive Real-Time Dynamic Programming. Encyclopedia of Machine Learning and Data Mining 2017, Springer

=External Links=
 * Andrew Barto from Wikipedia
 * Andrew Barto | LinkedIn
 * Andrew G. Barto, Department of Computer Science, University of Massachusetts Amherst
 * The Mathematics Genealogy Project - Andrew Barto

=References=

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