Fetching the paper…
Reading the bibliography…
Generative adversarial imitation learning (GAIL) has attracted increasing attention in the field of robot learning.
Pomerleau DA. Efficient training of artificial neural networks for autonomous navigation. Neural Computation. 1991;3
1991
Earlier work this paper cites.
Russell S. Learning agents for uncertain environments (extended abstract). In: Proceedings of the 11th annual conference on computational learning theory. 1998
1998
Earlier work this paper cites.
Abbeel P, Coates A, Quigley M, Ng AY. An application of reinforcement learning to aerobatic helicopter flight. 2007
2007
Earlier work this paper cites.
Ziebart BD, Maas A, Bagnell JA, Dey AK. Maximum entropy inverse reinforcement learning. Association for the Advancement of Artificial Intelligence. 2008;23
2008
Earlier work this paper cites.
Syed U, Bowling M, Schapire RE. Apprenticeship learning using linear programming. In: Proceedings of the 25th international conference on machine learning. 2008
2008
Earlier work this paper cites.
Argall BD, Chernovab S, Veloso M, Browning B. A survey of robot learning from demonstration. Robotics and Autonomous Systems. 2009;57
2009
Earlier work this paper cites.
Ross S, Gordon GJ, Bagnell D. A reduction of imitation learning and structured prediction to no-regret online learning. In: The 14th international conference on artificial intelligence and statistics. Vol. 15. 2011
2011
Earlier work this paper cites.
Goodfellow IJ, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y. Generative adversarial nets. In: Advances in neural information processing systems. Vol. 27. 2014
2014
Earlier work this paper cites.
Kingma DP, Ba J. Adam: A method for stochastic optimization. arXiv preprint arXiv:14126980. 2014;
2014
Earlier work this paper cites.
Schulman J, Levine S, Moritz P, Jordan M, Abbeel P. Trust region policy optimization. 2015
2015
Earlier work this paper cites.
Finn C, Christiano P, Abbeel P, Levine S. A connection between generative adversarial networks, inverse reinforcement learning, and energy-based models. arXiv preprint arXiv:161103852. 2016;
2016
Cited alongside, same era.
Ho J, Ermon S. Generative adversarial imitation learning. In: Advances in neural information processing systems. Vol. 29. 2016
2016
Cited alongside, same era.
Pfau D, Vinyals O. Connecting generative adversarial networks and actor-critic methods. In: Nips workshop on adversarial training. 2016
2016
Cited alongside, same era.
Chen X, Duan Y, Houthooft R, Schulman J, Sutskever I, Abbeel P. InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets. In: Advances in neural information processing systems. Vol. 29. 2016
2016
Cited alongside, same era.
Brockman G, Cheung V, Pettersson L, Schneider J, Schulman J, Tang J, Zaremba W. Openai gym. arXiv preprint arxiv:160601540. 2016;
Hausman K, Chebotar Y, Schaal S, Sukhatme G, Lim JJ. Multi-modal imitation learning from unstructured demonstrations using generative adversarial nets. In: Advances in neural information processing systems. Vol. 30. 2017
2017
Later among the works it cites.
Attia A, Dayan S. Global overview of imitation learning. arXiv preprint arXiv:180106503. 2018;
2018
Later among the works it cites.
Mueller C, Venicx J, Hayes B. Robust robot learning from demonstration and skill repair using conceptual constraints. In: 2018 ieee/rsj international conference on intelligent robots and systems (iros). IEEE. 2018. p. 6029–6036
2018
Later among the works it cites.
Sutton RS, Barto AG. Reinforcement learning: An introduction. MIT Press. 2018
2018
Later among the works it cites.
Justin Fu SL Katie Luo. Learning robust rewards with adversarial inverse reinforcement learning. In: International conference on learning representations. 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2016
Cited alongside, same era.
Li Y, Song J, Ermon S. InfoGAIL: Interpretable imitation learning from visual demonstrations. In: Advances in neural information processing systems. Vol. 30. 2017
2017
Cited alongside, same era.
Haarnoja T, Tang H, Abbeel P, Levine S. Reinforcement learning with deep energy-based policies. In: Proceedings of the 34th international conference on machine learning. Vol. 70. 2017
2017
Cited alongside, same era.
Nachum O, Norouzi M, Xu K, Schuurmans D. Bridging the gap between value and policy based reinforcement learning. In: Advances in neural information processing systems. Vol. 30. 2017
2017
Cited alongside, same era.
Merel J, Tassa Y, Srinivasan S, Lemmon J, Wang Z, Wayne G, Heess N. Learning human behaviors from motion capture by adversarial imitation. arXiv preprint arXiv:170702201. 2017;
2017
Cited alongside, same era.
2018
Later among the works it cites.
Henderson P, Chang WD, Bacon PL, Meger D, Pineau J, Precup D. Optiongan: Learning joint reward-policy options using generative adversarial inverse reinforcement learning. In: Thirty-second aaai conference on artificial intelligence. 2018
2018
Later among the works it cites.
Lin J, Zhang Z. ACGAIL: Imitation learning about multiple intentions with auxiliary classifier GANs. 2018
2018
Later among the works it cites.
Lynch C, Khansari M, Xiao T, Kumar V, Tompson J, Levine S, Sermanet P. Learning latent plans from play. arXiv preprint arXiv:190301973. 2019;
2019
Closest in time.
Xie A, Ebert F, Levine S, Finn C. Improvisation through physical understanding: Using novel objects as tools with visual foresight. arXiv preprint arXiv:190405538. 2019;
2019
Closest in time.