|
49
|
Reinforcement Learning And Its Application To Control
– Vijaykumar Gullapalli
- 1992
|
|
185
|
Learning and Sequential Decision Making
– Andrew G. Barto, R. S. Sutton, C. J. C. H. Watkins
- 1989
|
|
49
|
Learning and Problem Solving with Multilayer Connectionist Systems
– Charles William Anderson, Charles William Anderson
- 1986
|
|
472
|
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
|
|
1
|
A Tutorial on Reinforcement Learning Techniques
– Carlos Henrique, Costa Ribeiro
|
|
|
Aprendizado por Reforço
– Carlos Henrique Costa Ribeiro
- 1999
|
|
4
|
Reinforcement Learning Architectures
– Richard S. Sutton
- 1992
|
|
|
Learning to Control Dynamic Systems Via Associative Reinforcement Learning
– Vijaykumar Gullapalli
|
|
|
Introduction: The Challenge of Reinforcement Learning
– unknown authors
|
|
9
|
A Tutorial Survey of Reinforcement Learning
– S Sathiya Keerthi, B Ravindran
|
|
139
|
Interaction and Intelligent Behavior
– Maja J Mataric
- 1994
|
|
1060
|
Learning to predict by the methods of temporal differences
– Richard S. Sutton
- 1988
|
|
53
|
Adaptive Critics and the Basal Ganglia
– Andrew G. Barto
- 1995
|
|
|
Reinforcement Learning and Artificial Intelligence
– Richard S. Sutton
- 2003
|
|
1
|
Approximate Dynamic Programming- I: Modeling
– Warren B. Powell
|
