Learning to predict by the methods of temporal differences (1988)

by Richard S. Sutton
Venue:MACHINE LEARNING
Citations:1224 - 45 self

Active Bibliography

Manufactured in The Netherlands Learning to Predict by the Methods of Temporal Differences – Richard S. Sutton - 1987
195 Learning and Sequential Decision Making – Andrew G. Barto, R. S. Sutton, C. J. C. H. Watkins - 1989
51 Reinforcement Learning And Its Application To Control – Vijaykumar Gullapalli - 1992
Solution of Delayed Reinforcement Learning Problems Having Continuous Action Spaces – B. Ravindran - 1996
526 Learning to act using real-time dynamic programming – Andrew G. Barto, Steven J. Bradtke, Satinder P. Singh - 1993
1 Explorations of the Practical Issues of Learning Prediction-Control Tasks Using Temporal Difference Learning Methods – Charles L. Isbell, Charles L. Isbell, Charles L. Isbell - 1992
10 A Tutorial Survey of Reinforcement Learning – S Sathiya Keerthi, B Ravindran
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
1 C3 Reinforcement Learning – S. Sathiya Keerthi, B. Ravindran
69 Strategy Learning with Multilayer Connectionist Representations – Charles W. Anderson - 1987
17 Automated Learning of Load-Balancing Strategies For A Distributed Computer System – P. Mehra, Load Balancing As, A Strategy-learning Task - 1992
Load Balancing as a Strategiy-Learning Task – n.n. - 1992
11 On the Reduction of Costs for Robot Controller Synthesis – Attilio Giordana, Michael Kaiser, Marnix Nuttin - 1994
3 The convergence of TD(X) for general k – Peter Dayan - 1992
4 Robot Learning - Three case studies in Robotics and Machine Learning – M. Kaiser, L. Camarinha-Matos, A. Giordana, V. Klingspor J. del R. Millán, V. Klingspor, J. Del R. Mill An, R. Suárez, F. G. B. De Natale, M. Nuttin, R. Su Arez, Prof Dr. -ing, R. Dillmann - 1994
3 Reinforcement Learning Algorithms as Function Optimizers – Ronald J. Williams, Jing Peng - 1989
49 Learning to Solve Markovian Decision Processes – Satinder P. Singh - 1994
20 Incremental Dynamic Programming for On-Line Adaptive Optimal Control – Steven J. Bradtke - 1994
10 Modular On-line Function Approximation for Scaling up Reinforcement Learning – Chen Khong Tham - 1994