Fetching the paper…
Reading the bibliography…
This paper explores a simple regularizer for reinforcement learning by proposing Generative Adversarial Self-Imitation Learning (GASIL), which encourages the agent to imitate past good trajectories via generative adversarial imitation learning framework.
Q-learning
Christopher JCH Watkins and Peter Dayan · 1992
Earlier work this paper cites.
Policy invariance under reward transformations: Theory and application to reward shaping
Andrew Y Ng, Daishi Harada, and Stuart Russell · 1999
Earlier work this paper cites.
Hippocampal contributions to control: the third way
Máté Lengyel and Peter Dayan · 2008
Earlier work this paper cites.
Apprenticeship learning using linear programming
Umar Syed, Michael Bowling, and Robert E Schapire · 2008
Earlier work this paper cites.
Maximum entropy inverse reinforcement learning
Brian D Ziebart, Andrew L Maas, J Andrew Bagnell, and Anind K Dey · 2008
Earlier work this paper cites.
Where do rewards come from
Satinder Singh, Richard L Lewis, and Andrew G Barto · 2009
Earlier work this paper cites.
Reward design via online gradient ascent
Jonathan Sorg, Richard L Lewis, and Satinder P Singh · 2010
Earlier work this paper cites.
Mujoco: A physics engine for model-based control
Emanuel Todorov, Tom Erez, and Yuval Tassa · 2012
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2015
Earlier work this paper cites.
Charles Blundell, Benigno Uria, Alexander Pritzel, Yazhe Li, Avraham Ruderman, Joel Z Leibo, Jack Rae, Daan Wierstra, and Demis Hassabis · 2016
Earlier work this paper cites.
Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, and Wojciech Zaremba · 2016
Cited alongside, same era.
Deep learning for reward design to improve monte carlo tree search in atari games
Xiaoxiao Guo, Satinder P. Singh, Richard L. Lewis, and Honglak Lee · 2016
Cited alongside, same era.
Generative adversarial imitation learning
Jonathan Ho and Stefano Ermon · 2016
Cited alongside, same era.
Neural symbolic machines: Learning semantic parsers on freebase with weak supervision
Chen Liang, Jonathan Berant, Quoc Le, Kenneth D Forbus, and Ni Lao · 2016
Cited alongside, same era.
Generative adversarial text to image synthesis
Scott Reed, Zeynep Akata, Xinchen Yan, Lajanugen Logeswaran, Bernt Schiele, and Honglak Lee · 2016
Simple nearest neighbor policy method for continuous control tasks
Elman Mansimov and Kyunghyun Cho · 2017
Later among the works it cites.
Alexander Pritzel, Benigno Uria, Sriram Srinivasan, Adrià Puigdomènech, Oriol Vinyals, Demis Hassabis, Daan Wierstra, and Charles Blundell · 2017
Later among the works it cites.
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
Later among the works it cites.
Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
End-to-end differentiable adversarial imitation learning
Nir Baram, Oron Anschel, Itai Caspi, and Shie Mannor · 2017
Cited alongside, same era.
Openai baselines
Prafulla Dhariwal, Christopher Hesse, Oleg Klimov, Alex Nichol, Matthias Plappert, Alec Radford, John Schulman, Szymon Sidor, and Yuhuai Wu · 2017
Cited alongside, same era.
Reinforcement learning with deep energy-based policies
Tuomas Haarnoja, Haoran Tang, Pieter Abbeel, and Sergey Levine · 2017
Cited alongside, same era.
Multi-modal imitation learning from unstructured demonstrations using generative adversarial nets
Karol Hausman, Yevgen Chebotar, Stefan Schaal, Gaurav Sukhatme, and Joseph J Lim · 2017
Cited alongside, same era.
Infogail: Interpretable imitation learning from visual demonstrations
Yunzhu Li, Jiaming Song, and Stefano Ermon · 2017
Cited alongside, same era.
Daniel A Abolafia, Mohammad Norouzi, and Quoc V Le · 2018
Closest in time.
Learning self-imitating diverse policies
Tanmay Gangwani, Qiang Liu, and Jian Peng · 2018
Closest in time.
Recall traces: Backtracking models for efficient reinforcement learning
Anirudh Goyal, Philemon Brakel, William Fedus, Timothy Lillicrap, Sergey Levine, Hugo Larochelle, and Yoshua Bengio · 2018
Closest in time.
Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine · 2018
Closest in time.
Self-imitation learning
Junhyuk Oh, Yijie Guo, Satinder Singh, and Honglak Lee · 2018
Closest in time.
On learning intrinsic rewards for policy gradient methods
Zeyu Zheng, Junhyuk Oh, and Satinder Singh · 2018
Closest in time.