Reinforcement Learning
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TOTAL DOCUMENTS

8

(FIVE YEARS 0)

H-INDEX

4

(FIVE YEARS 0)

Published By Springer US

9781461366089, 9781461536185

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

A Reinforcement Connectionist Approach to Robot Path Finding in Non-Maze-Like Environments

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_8 ◽

1992 ◽

pp. 139-171 ◽

Cited By ~ 2

Author(s):

José R. Millán ◽

Carme Torras

Keyword(s):

Path Finding ◽

Connectionist Approach ◽

Robot Path

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Practical Issues in Temporal Difference Learning

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_3 ◽

1992 ◽

pp. 33-53 ◽

Cited By ~ 28

Author(s):

Gerald Tesauro

Keyword(s):

Temporal Difference ◽

Temporal Difference Learning

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Technical Note

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_4 ◽

1992 ◽

pp. 55-68 ◽

Cited By ~ 36

Author(s):

Christopher J. C. H. Watkins ◽

Peter Dayan

Keyword(s):

Technical Note

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The Convergence of TD(λ) for General λ

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_7 ◽

1992 ◽

pp. 117-138 ◽

Cited By ~ 1

Author(s):

Peter Dayan

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Transfer of Learning by Composing Solutions of Elemental Sequential Tasks

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_6 ◽

1992 ◽

pp. 99-115 ◽

Cited By ~ 3

Author(s):

Satinder Pal Singh

Keyword(s):

Transfer Of Learning

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Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_2 ◽

1992 ◽

pp. 5-32 ◽

Cited By ~ 72

Author(s):

Ronald J. Williams

Keyword(s):

Reinforcement Learning ◽

Statistical Gradient

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Introduction: The Challenge of Reinforcement Learning

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_1 ◽

1992 ◽

pp. 1-3 ◽

Cited By ~ 12

Author(s):

Richard S. Sutton

Keyword(s):

Reinforcement Learning

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Self-Improving Reactive Agents Based on Reinforcement Learning, Planning and Teaching

Reinforcement Learning ◽

10.1007/978-1-4615-3618-5_5 ◽

1992 ◽

pp. 69-97 ◽

Cited By ~ 4

Author(s):

Long-Ji Lin

Keyword(s):

Reinforcement Learning ◽

Reactive Agents

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