Andrew Barto

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Richard S. SuttonDeepMind, Amii, and University of AlbertaVerified email at richsutton.com
George KonidarisBrownVerified email at cs.brown.edu
Roderic GrupenUniversity of MassachusettsVerified email at cs.umass.edu
Charles Andersonprofessor of computer science, Colorado State University. Founder Pattern Exploration, LLC.Verified email at colostate.edu
Scott KuindersmaSenior Director of Robotics Research at Boston DynamicsVerified email at seas.harvard.edu
Andrew FaggUniversity of OklahomaVerified email at cs.ou.edu
Scott NiekumAssociate Professor, University of Massachusetts AmherstVerified email at cs.umass.edu
Özgür ŞimşekUniversity of BathVerified email at bath.ac.uk
Steven BradtkeResearch Engineer, Vistronix, Inc.Verified email at asrcfederal.com
Sridhar MahadevanDirector, Data Science Lab, Adobe Research & Professor, University of Massachusetts, AmherstVerified email at cs.umass.edu
Amy McGovernUniversity of OklahomaVerified email at ou.edu
Theodore J. PerkinsOttawa Hospital Research InstituteVerified email at ohri.ca
Richard L. LewisProfessor of Psychology, Linguistics and Cognitive Science, University of MichiganVerified email at umich.edu
Gianluca BaldassarreSenior Researcher, Institute of Cognitive Sciences and Tecnologies, Italian National ResearchVerified email at istc.cnr.it
Balaraman RavindranProfessor of Computer Science, Indian Institute of Technology MadrasVerified email at cse.iitm.ac.in
Sarah OsentoskiIron OxVerified email at ironox.com
Nuttapong ChentanezNVIDIA, Chulalongkorn UniversityVerified email at eecs.berkeley.edu
Marco MirolliResearcher, Istituto di Scienze e Tecnologie della Cognizione, CNR, ItalyVerified email at istc.cnr.it
Alicia WolfePostdoc, Wesleyan UniversityVerified email at wesleyan.edu
Matthew BotvinickGoogle DeepMind, Yale Law School, University College LondonVerified email at google.com

Andrew Barto

University of Massachusetts Amherst

Verified email at cs.umass.edu - Homepage

Reinforcement learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Reinforcement learning: An introduction RS Sutton, AG Barto MIT press, 2018	64279	2018
Introduction to reinforcement learning RS Sutton, AG Barto MIT press 135, 223-260, 1998	5462	1998
Neuronlike adaptive elements that can solve difficult learning control problems AG Barto, RS Sutton, CW Anderson IEEE transactions on systems, man, and cybernetics, 834-846, 1983	4833	1983
Toward a modern theory of adaptive networks: expectation and prediction. RS Sutton, AG Barto Psychological review 88 (2), 135, 1981	1773	1981
Learning to act using real-time dynamic programming AG Barto, SJ Bradtke, SP Singh Artificial intelligence 72 (1-2), 81-138, 1995	1613	1995
Recent advances in hierarchical reinforcement learning AG Barto, S Mahadevan Discrete event dynamic systems 13 (1-2), 41-77, 2003	1610	2003
Introduction to reinforcement learning. Vol. 135 RS Sutton, AG Barto MIT press Cambridge 5, 21-22, 1998	992	1998
Intrinsically motivated reinforcement learning N Chentanez, A Barto, S Singh Advances in neural information processing systems 17, 2004	964	2004
Linear least-squares algorithms for temporal difference learning SJ Bradtke, AG Barto Machine learning 22, 33-57, 1996	945	1996
Handbook of learning and approximate dynamic programming J Si, AG Barto, WB Powell, D Wunsch John Wiley & Sons, 2004	939	2004
Improving elevator performance using reinforcement learning R Crites, A Barto Advances in neural information processing systems 8, 1995	876	1995
Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks RA Jacobs, MI Jordan, AG Barto Cognitive science 15 (2), 219-250, 1991	791	1991
Time-derivative models of pavlovian reinforcement. RS Sutton, AG Barto The MIT Press, 1990	770	1990
Reinforcement learning is direct adaptive optimal control RS Sutton, AG Barto, RJ Williams IEEE control systems magazine 12 (2), 19-22, 1992	765	1992
Reinforcement learning: An introduction (adaptive computation and machine learning) AG Barto, RS Sutton MIT press, 1998	740	1998
Adaptive critics and the basal ganglia AG Barto	736*	1995
Learning and sequential decision making AG Barto, RS Sutton, C Watkins University of Massachusetts, 1989	640	1989
Automatic discovery of subgoals in reinforcement learning using diverse density A McGovern, AG Barto	615	2001
Adaptive control of duty cycling in energy-harvesting wireless sensor networks CM Vigorito, D Ganesan, AG Barto 2007 4th Annual IEEE communications society conference on sensor, mesh and …, 2007	554	2007
Intrinsically motivated learning of hierarchical collections of skills AG Barto, S Singh, N Chentanez Proceedings of the 3rd International Conference on Development and Learning …, 2004	545	2004

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