Demonstration-based Reinforcement Learning
Demonstration-Based Reinforcement Learning is a reinforcement learning paradigm that belongs to the class of imitation learning methods, distinguished by its use of expert demonstrations to guide policy acquisition through reward shaping or direct policy initialization.
81
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4.1K
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241
Authors
86
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2017–2026
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Deep Q-learning From Demonstrations
Todd Hester, Matej Vecerík, Olivier Pietquin et al. · Proceedings of the AAAI Conference on Artificial Intelligence · 2018 · 809 citations · Full text
Deep Q-learning from Demonstrations
Todd Hester, Matej Vecerík, Olivier Pietquin et al. · arXiv (Cornell University) · 2017 · 307 citations · Full text
Reinforcement learning from demonstration through shaping
Tim Brys, Anna Harutyunyan, Halit Bener Suay et al. · 2015 · 157 citations
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Google (United States)
Mountain View, United States
4 h-index
32 publications
15.7K citations

Worcester Polytechnic Institute
Worcester, United States
4 h-index
10 publications
732 citations
The University of Texas at Austin
Austin, United States
4 h-index
10 publications
558 citations
Max Planck Institute for Software Systems
Saarbrücken, Germany
4 h-index
11 publications
313 citations
Georgia Institute of Technology
Atlanta, United States
3 h-index
10 publications
307 citations

Washington State University
Pullman, United States
3 h-index
5 publications
275 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
11 publications
364 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
10 publications
418 citations
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Repository · 10 publications · 761 citations
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Conference · 6 publications · 953 citations
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2 publications · 59 citations
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Conference · 2 publications · 85 citations
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2 publications · 65 citations
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