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Q-learning

Q-learning Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian domains. It amounts to an incremental method for dynamic programming which imposes limited computational demands. It works by successively improving its evaluations of the quality of particular actions at particular states. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Machine Learning Springer Journals

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References (18)

Publisher
Springer Journals
Copyright
Copyright
Subject
Computer Science; Artificial Intelligence; Control, Robotics, Mechatronics; Artificial Intelligence; Simulation and Modeling; Natural Language Processing (NLP)
ISSN
0885-6125
eISSN
1573-0565
DOI
10.1007/BF00992698
Publisher site
See Article on Publisher Site

Abstract

Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian domains. It amounts to an incremental method for dynamic programming which imposes limited computational demands. It works by successively improving its evaluations of the quality of particular actions at particular states.

Journal

Machine LearningSpringer Journals

Published: Dec 30, 2004

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