Multi-objective Temporal Difference Learning
Multi-Objective Temporal Difference Learning is a reinforcement learning method that extends classical Temporal Difference Learning to handle multiple conflicting objectives by learning a set of value functions or policies that approximate the Pareto optimal frontier in stochastic environments modeled as Multi-Objective Markov Decision Processes.
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1.6K
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22
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17
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2017–2026
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Practical issues in temporal difference learning
Gerald Tesauro · Machine Learning · 1992 · 800 citations · Full text
Average cost temporal-difference learning
John N. Tsitsiklis, Benjamin Van Roy · Automatica · 1999 · 142 citations
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Massachusetts Institute of Technology, United States
2 publications · 172 citations
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IBM Research - Thomas J. Watson Research Center
Yorktown Heights, United States
2 h-index
2 publications
839 citations
Massachusetts Institute of Technology
Cambridge, United States
2 h-index
4 publications
344 citations
Vrije Universiteit Brussel
Brussels, Belgium
2 h-index
4 publications
552 citations
Lorestan University
Khorramabad, Iran
1 h-index
2 publications
256 citations
Université Constantine 2
Constantine, Algeria
1 h-index
1 publications
18 citations
Institute of Automation
Beijing, China
1 h-index
1 publications
68 citations
Decision Systems (United States)
Northbrook, United States
1 h-index
2 publications
60 citations
The University of Tokyo
Tokyo, Japan
1 h-index
1 publications
22 citations
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2 publications · 839 citations
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1 publications · 68 citations
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1 publications · 18 citations
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1 publications · 142 citations
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1 publications · 22 citations
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