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The goal of this work is to address the recent success of domain randomization and data augmentation for the sim2real setting.
M. Arjovsky, L. Bottou, I. Gulrajani and D. Lopez-Paz · 1907
Earlier work this paper cites.
“Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning”
Tianhe Yu et al · 1910
Earlier work this paper cites.
“Bisimulation through Probabilistic Testing (Preliminary Report)”
K.. Larsen and A. Skou · 1989
Earlier work this paper cites.
“Principles of Risk Minimization for Learning Theory”
V. Vapnik · 1992
Earlier work this paper cites.
“Towards Quantitative Verification of Probabilistic Transition Systems”
Franck van Breugel and James Worrell · 2001
Earlier work this paper cites.
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David Krueger et al · 2003
Earlier work this paper cites.
“Equivalence notions and model minimization in Markov decision processes”
Robert Givan, Thomas. Dean and Matthew Greig · 2003
Earlier work this paper cites.
“Topics in optimal transportation”
C“’edric Villani · 2003
Earlier work this paper cites.
“Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels”, 2020
Ilya Kostrikov, Denis Yarats and Rob Fergus · 2004
Earlier work this paper cites.
“Reinforcement Learning with Augmented Data”, 2020
Michael Laskin et al · 2004
Earlier work this paper cites.
“Towards a Unified Theory of State Abstraction for MDPs”
Lihong Li, Thomas Walsh and Michael Littman · 2006
Earlier work this paper cites.
“Learning Invariant Representations for Reinforcement Learning without Reconstruction”, 2020
Amy Zhang et al · 2006
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Kanishka Rao et al · 2006
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Norm Ferns, Prakash Panangaden and Doina Precup · 2011
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“Bisimulation Metrics are Optimal Value Functions.”
Norman Ferns and Doina Precup · 2014
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Alex Lee, Anusha Nagabandi, Pieter Abbeel and Sergey Levine · 2019
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“Dream to control: Learning behaviors by latent imagination”
Danijar Hafner, Timothy Lillicrap, Jimmy Ba and Mohammad Norouzi · 2019
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“Invariant Causal Prediction for Block MDPs”
Amy Zhang et al · 2020
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