Batch Policy Iteration
Batch Policy Iteration is a reinforcement learning algorithm that, within the class of policy iteration methods, updates the policy using a fixed batch of data collected from prior interactions with the environment, thereby decoupling the data collection process from the policy improvement steps.
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Institutions
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2017–2026
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Towards Industrial Robot Learning from Demonstration
Wilson Ko, Yan Wu, Keng Peng Tee et al. · 2015 · 22 citations
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Institut National des Sciences Appliquées Rouen Normandie, France
1 publications · 11 citations
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1–5 of 22
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University of Alberta
Edmonton, Canada
2 h-index
3 publications
52 citations

University of Massachusetts Amherst
Amherst Center, United States
1 h-index
1 publications
96 citations
Adobe Systems (United States)
San Jose, United States
1 h-index
2 publications
192 citations
Shanghai University of Engineering Science
Shanghai, China
1 h-index
3 publications
75 citations
Université de Lille
Lille, France
1 h-index
1 publications
30 citations
Beijing Jiaotong University
Beijing, China
1 h-index
1 publications
25 citations

Hungarian Academy of Sciences
Budapest, Hungary
1 h-index
2 publications
60 citations
Agency for Science, Technology and Research
Singapore, Singapore
1 h-index
2 publications
44 citations
1–8 of 19
1 publications · 39 citations
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1 publications · 25 citations
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1 publications · 11 citations
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Conference · 1 publications · 96 citations
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Conference · 1 publications · 11 citations
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