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Learning to perform tasks by leveraging a dataset of expert observations, also known as imitation learning from observations (ILO), is an important paradigm for learning skills without access to the expert reward function or the expert actions.
Optimization and sensitivity analysis of computer simulation models by the score function method
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A game-theoretic approach to apprenticeship learning
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Apprenticeship learning using linear programming
Umar Syed, Michael Bowling, and Robert E Schapire · 2008
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Modeling purposeful adaptive behavior with the principle of maximum causal entropy
Brian D Ziebart · 2010
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A reduction of imitation learning and structured prediction to no-regret online learning
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Mujoco: A physics engine for model-based control
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A universally consistent spectral estimator for the support of a distribution
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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High-dimensional continuous control using generalized advantage estimation
John Schulman, Philipp Moritz, Sergey Levine, Michael Jordan, and Pieter Abbeel · 2015
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Deep variational information bottleneck
Alexander A Alemi, Ian Fischer, Joshua V Dillon, and Kevin Murphy · 2016
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Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
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Chelsea Finn, Paul Christiano, Pieter Abbeel, and Sergey Levine · 2016
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Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
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Learning invariant feature spaces to transfer skills with reinforcement learning
Abhishek Gupta, Coline Devin, YuXuan Liu, Pieter Abbeel, and Sergey Levine · 2017
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Learning human behaviors from motion capture by adversarial imitation
Josh Merel, Yuval Tassa, Dhruva TB, Sriram Srinivasan, Jay Lemmon, Ziyu Wang, Greg Wayne, and Nicolas Heess · 2017
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Time-contrastive networks: Self-supervised learning from video
Pierre Sermanet, Corey Lynch, Yevgen Chebotar, Jasmine Hsu, Eric Jang, Stefan Schaal, Sergey Levine, and Google Brain · 2018
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Disagreement-regularized imitation learning
Kiante Brantley, Wen Sun, and Mikael Henaff · 2019
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Imitating latent policies from observation
Ashley Edwards, Himanshu Sahni, Yannick Schroecker, and Charles Isbell · 2019
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Imitation learning as f f -divergence minimization
Liyiming Ke, Matt Barnes, Wen Sun, Gilwoo Lee, Sanjiban Choudhury, and Siddhartha Srinivasa · 2019
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State alignment-based imitation learning
Fangchen Liu, Zhan Ling, Tongzhou Mu, and Hao Su · 2019
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John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Third-person imitation learning
Bradly C Stadie, Pieter Abbeel, and Ilya Sutskever · 2017
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Robust imitation of diverse behaviors
Ziyu Wang, Josh Merel, Scott Reed, Greg Wayne, Nando de Freitas, and Nicolas Heess · 2017
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Exploration by random network distillation
Yuri Burda, Harrison Edwards, Amos Storkey, and Oleg Klimov · 2018
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Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
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Imitation from observation: Learning to imitate behaviors from raw video via context translation
YuXuan Liu, Abhishek Gupta, Pieter Abbeel, and Sergey Levine · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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Xue Bin Peng, Angjoo Kanazawa, Sam Toyer, Pieter Abbeel, and Sergey Levine · 2018
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Provably efficient imitation learning from observation alone
Wen Sun, Anirudh Vemula, Byron Boots, and Drew Bagnell · 2019
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Random expert distillation: Imitation learning via expert policy support estimation
Ruohan Wang, Carlo Ciliberto, Pierluigi Vito Amadori, and Yiannis Demiris · 2019
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Imitation learning from observations by minimizing inverse dynamics disagreement
Chao Yang, Xiaojian Ma, Wenbing Huang, Fuchun Sun, Huaping Liu, Junzhou Huang, and Chuang Gan · 2019
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Reinforced imitation in heterogeneous action space
Konrad Zolna, Negar Rostamzadeh, Yoshua Bengio, Sungjin Ahn, and Pedro O Pinheiro · 2019
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Reparameterized variational divergence minimization for stable imitation
Dilip Arumugam, Debadeepta Dey, Alekh Agarwal, Asli Celikyilmaz, Elnaz Nouri, and Bill Dolan · 2020
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State-only imitation with transition dynamics mismatch
Tanmay Gangwani and Jian Peng · 2020
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Off-policy imitation learning from observations
Zhuangdi Zhu, Kaixiang Lin, Bo Dai, and Jiayu Zhou · 2021
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