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Imitation learning (IL) has achieved considerable success in solving complex sequential decision-making problems.
Efficient Training of Artificial Neural Networks for Autonomous Navigation
Pomerleau, D. 1991 · 1991
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Algorithms for Inverse Reinforcement Learning
Ng, A. Y.; and Russell, S. 2000 · 2000
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Apprenticeship learning via inverse reinforcement learning
Abbeel, P.; and Ng, A. Y. 2004 · 2004
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The Sinkhorn–Knopp algorithm: convergence and applications
Knight, P. A. 2008 · 2008
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Maximum Entropy Inverse Reinforcement Learning
Ziebart, B. D.; Maas, A. L.; Bagnell, J. A.; and Dey, A. K. 2008 · 2008
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Efficient Reductions for Imitation Learning
Ross, S.; and Bagnell, D. 2010 · 2010
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A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Ross, S.; Gordon, G. J.; and Bagnell, D. 2011 · 2011
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, K.; Vedaldi, A.; and Zisserman, A. 2013 · 2013
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Generative Adversarial Nets
Goodfellow, I. J.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A. C.; and Bengio, Y. 2014 · 2014
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Generative adversarial imitation learning
Ho, J.; and Ermon, S. 2016 · 2016
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End-to-end differentiable adversarial imitation learning
Baram, N.; Anschel, O.; Caspi, I.; and Mannor, S. 2017 · 2017
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Imitation Learning: A Survey of Learning Methods
Hussein, A.; Gaber, M. M.; Elyan, E.; and Jayne, C. 2017 · 2017
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Learning Robust Rewards with Adverserial Inverse Reinforcement Learning
Fu, J.; Luo, K.; and Levine, S. 2018 · 2018
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Addressing function approximation error in actor-critic methods
Fujimoto, S.; Hoof, H.; and Meger, D. 2018 · 2018
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Lifelong Inverse Reinforcement Learning
Mendez, J. A.; Shivkumar, S.; and Eaton, E. 2018 · 2018
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Tassa, Y.; Doron, Y.; Muldal, A.; Erez, T.; Li, Y.; Casas, D. d. L.; Budden, D.; Abdolmaleki, A.; Merel, J.; Lefrancq, A.; et al. 2018 · 2018
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Behavioral Cloning from Observation
Torabi, F.; Warnell, G.; and Stone, P. 2018a · 2018
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Learning Latent Dynamics for Planning from Pixels
Hafner, D.; Lillicrap, T. P.; Fischer, I.; Villegas, R.; Ha, D.; Lee, H.; and Davidson, J. 2019 · 2019
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Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning
Kostrikov, I.; Agrawal, K. K.; Dwibedi, D.; Levine, S.; and Tompson, J. 2019 · 2019
Cited alongside, same era.
Sample efficient reinforcement learning through learning from demonstrations in minecraft
Scheller, C.; Schraner, Y.; and Vogel, M. 2020 · 2019
Cited alongside, same era.
Model-based Behavioral Cloning with Future Image Similarity Learning
Wu, A.; Piergiovanni, A. J.; and Ryoo, M. S. 2019 · 2019
Cited alongside, same era.
Disagreement-Regularized Imitation Learning
Brantley, K.; Sun, W.; and Henaff, M. 2020 · 2020
Cited alongside, same era.
Dream to Control: Learning Behaviors by Latent Imagination
Hafner, D.; Lillicrap, T. P.; Ba, J.; and Norouzi, M. 2020 · 2020
Cited alongside, same era.
Urban Driving with Conditional Imitation Learning
Adversarial inverse reinforcement learning with self-attention dynamics model
Sun, J.; Yu, L.; Dong, P.; Lu, B.; and Zhou, B. 2021 · 2021
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Robust Navigation for Racing Drones based on Imitation Learning and Modularization
Wang, T.; and Chang, D. E. 2021 · 2021
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Image Augmentation Is All You Need: Regularizing Deep Reinforcement Learning from Pixels
Yarats, D.; Kostrikov, I.; and Fergus, R. 2021 · 2021
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Video PreTraining (VPT): Learning to Act by Watching Unlabeled Online Videos
Baker, B.; Akkaya, I.; Zhokov, P.; Huizinga, J.; Tang, J.; Ecoffet, A.; Houghton, B.; Sampedro, R.; and Clune, J. 2022 · 2022
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Robust Imitation Learning against Variations in Environment Dynamics
Chae, J.; Han, S.; Jung, W.; Cho, M.; Choi, S.; and Sung, Y. 2022 · 2022
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Hawke, J.; Shen, R.; Gurau, C.; Sharma, S.; Reda, D.; Nikolov, N.; Mazur, P.; Micklethwaite, S.; Griffiths, N.; Shah, A.; and Kendall, A. 2020 · 2020
Cited alongside, same era.
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty
Hendrycks, D.; Mu, N.; Cubuk, E. D.; Zoph, B.; Gilmer, J.; and Lakshminarayanan, B. 2020 · 2020
Cited alongside, same era.
Domain adaptive imitation learning
Kim, K.; Gu, Y.; Song, J.; Zhao, S.; and Ermon, S. 2020 · 2020
Cited alongside, same era.
CURL: Contrastive Unsupervised Representations for Reinforcement Learning
Laskin, M.; Srinivas, A.; and Abbeel, P. 2020 · 2020
Cited alongside, same era.
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Sohn, K.; Berthelot, D.; Carlini, N.; Zhang, Z.; Zhang, H.; Raffel, C.; Cubuk, E. D.; Kurakin, A.; and Li, C. 2020 · 2020
Cited alongside, same era.
Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning
Yu, T.; Quillen, D.; He, Z.; Julian, R.; Hausman, K.; Finn, C.; and Levine, S. 2020 · 2020
Cited alongside, same era.
A survey of inverse reinforcement learning: Challenges, methods and progress
Arora, S.; and Doshi, P. 2021 · 2021
Cited alongside, same era.
Chen, X.; Toyer, S.; Wild, C.; Emmons, S.; Fischer, I.; Lee, K.; Alex, N.; Wang, S. H.; Luo, P.; Russell, S.; Abbeel, P.; and Shah, R. 2022 · 2022
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Ghugare, R.; Bharadhwaj, H.; Eysenbach, B.; Levine, S.; and Salakhutdinov, R. 2022 · 2022
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Robust Imitation via Mirror Descent Inverse Reinforcement Learning
Han, D.; Kim, H.; Lee, H.; Ryu, J.; and Zhang, B. 2022 · 2022
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Model-Based Imitation Learning for Urban Driving
Hu, A.; Corrado, G.; Griffiths, N.; Murez, Z.; Gurau, C.; Yeo, H.; Kendall, A.; Cipolla, R.; and Shotton, J. 2022 · 2022
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Imitation learning with sinkhorn distances
Papagiannis, G.; and Li, Y. 2023 · 2022
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Masked World Models for Visual Control
Seo, Y.; Hafner, D.; Liu, H.; Liu, F.; James, S.; Lee, K.; and Abbeel, P. 2022 · 2022
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Behavior Transformers: Cloning $k$ modes with one stone
Shafiullah, N. M.; Cui, Z. J.; Altanzaya, A.; and Pinto, L. 2022 · 2022
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Maximum-Likelihood Inverse Reinforcement Learning with Finite-Time Guarantees
Zeng, S.; Li, C.; Garcia, A.; and Hong, M. 2022 · 2022
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Watch and match: Supercharging imitation with regularized optimal transport
Haldar, S.; Mathur, V.; Yarats, D.; and Pinto, L. 2023 · 2023
Closest in time.
Visual Imitation Learning with Patch Rewards
Liu, M.; He, T.; Zhang, W.; Yan, S.; and Xu, Z. 2023 · 2023
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SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models
Wan, S.; Wang, Y.; Shao, M.; Chen, R.; and Zhan, D.-C. 2023 · 2023
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Become a Proficient Player with Limited Data through Watching Pure Videos
Ye, W.; Zhang, Y.; Abbeel, P.; and Gao, Y. 2023 · 2023
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