Reinforcement Learning I: Introduction (1998)

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by Richard S. Sutton , Andrew G. Barto
Citations:3755 - 98 self

Active Bibliography

51 Reinforcement Learning And Its Application To Control – Vijaykumar Gullapalli - 1992
195 Learning and Sequential Decision Making – Andrew G. Barto, R. S. Sutton, C. J. C. H. Watkins - 1989
54 Learning and Problem Solving with Multilayer Connectionist Systems – Charles William Anderson - 1986
527 Learning to act using real-time dynamic programming – Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh - 1993
Approximately as appeared in: Learning and Computational Neuroscience: Foundations of Adaptive Networks, M. Gabriel and J. Moore, Eds., pp. 497--537. MIT Press, 1990. – Chapter Time-Derivative Models, Richard S. Sutton, Andrew G. Barto - 1990
3 The convergence of TD(X) for general k – Peter Dayan - 1992
6 The Convergence of TD(λ) for General λ – Peter Dayan - 1992
4 Reinforcement Learning in Non-Markov Environments – Steven D. Whitehead, Long Ji Lin - 1992
Aprendizado por Refor├žo – Carlos Henrique Costa Ribeiro - 1999
2 A Tutorial on Reinforcement Learning Techniques – Carlos Henrique Costa Ribeiro
4 Reinforcement Learning Architectures – Richard S. Sutton - 1992
Learning to Control Dynamic Systems Via Associative Reinforcement Learning – Vijaykumar Gullapalli
1 C3 Reinforcement Learning – S. Sathiya Keerthi, B. Ravindran
10 A Tutorial Survey of Reinforcement Learning – S Sathiya Keerthi, B Ravindran
Introduction: The Challenge of Reinforcement Learning – unknown authors
146 Interaction and Intelligent Behavior – Maja J Mataric - 1994
1226 Learning to predict by the methods of temporal differences – Richard S. Sutton - 1988
80 Adaptive Critics and the Basal Ganglia – Andrew G. Barto - 1995
2 Reinforcement Learning and Artificial Intelligence – Richard S. Sutton - 2003