rl-paper-study/2nd at main · utilForever/rl-paper-study · GitHub

Name		Name	Last commit message	Last commit date
parent directory ..
200727 - Deep Recurrent Q-Learning for Partially Observable MDPs, M. Hausknecht et al, 2015.pdf		200727 - Deep Recurrent Q-Learning for Partially Observable MDPs, M. Hausknecht et al, 2015.pdf
200803 - Hierarchical Visuomotor Control of Humanoids, J. Merel et al, 2018.pdf		200803 - Hierarchical Visuomotor Control of Humanoids, J. Merel et al, 2018.pdf
200810 - Deep Reinforcement Learning with a Natural Language Action Space, J. He et al, 2015.pdf		200810 - Deep Reinforcement Learning with a Natural Language Action Space, J. He et al, 2015.pdf
200810 - Learning Dexterous In-Hand Manipulation, M. Andrychowicz et al, 2020.pdf		200810 - Learning Dexterous In-Hand Manipulation, M. Andrychowicz et al, 2020.pdf
200810 - Program Guided Agent, SH. Sun et al, 2020.pdf		200810 - Program Guided Agent, SH. Sun et al, 2020.pdf
200824 - Trust Region Policy Optimization, Schulman et al, 2015.pdf		200824 - Trust Region Policy Optimization, Schulman et al, 2015.pdf
200831 - Implementation Matters in Deep RL A Case Study on PPO and TRPO, L. Engstrom et al, 2020.pdf		200831 - Implementation Matters in Deep RL A Case Study on PPO and TRPO, L. Engstrom et al, 2020.pdf
200831 - Proximal Policy Optimization Algorithms, Schulman et al, 2017.pdf		200831 - Proximal Policy Optimization Algorithms, Schulman et al, 2017.pdf
200907 - Generative Adversarial Imitation Learning, J. Ho et al, 2016.pdf		200907 - Generative Adversarial Imitation Learning, J. Ho et al, 2016.pdf
200914 - Efficient Reductions for Imitation Learning, S. Ross et al, 2010.pdf		200914 - Efficient Reductions for Imitation Learning, S. Ross et al, 2010.pdf
200914 - Grandmaster Level in StarCraft II using Multi-agent Reinforcement Learning, O. Vinyals et al, 2019.pdf		200914 - Grandmaster Level in StarCraft II using Multi-agent Reinforcement Learning, O. Vinyals et al, 2019.pdf
200914 - Variational Discriminator Bottleneck Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow, XB. Peng et al, 2018.pdf		200914 - Variational Discriminator Bottleneck Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow, XB. Peng et al, 2018.pdf
README.md		README.md

README.md

2nd Study Paper List

Date	Paper	Presenter	Links
7/27	Deep Recurrent Q-Learning for Partially Observable MDPs, M. Hausknecht et al, 2015.	Minsuk Sung	[paper] [review]
8/3	Hierarchical Visuomotor Control of Humanoids, J. Merel et al, 2018.	Seonghyeon Moon	[paper] [review]
8/10	Learning Dexterous In-Hand Manipulation, M. Andrychowicz et al, 2020.	Ingyun Ahn	[paper] [review]
8/10	Deep Reinforcement Learning with a Natural Language Action Space, J. He et al, 2015.	Jihun Kim	[paper] [review]
8/10	Program Guided Agent, SH. Sun et al, 2020.	Haneul Choi	[paper] [review]
8/24	Trust Region Policy Optimization, J. Schulman et al, 2015.	Chris Ohk	[paper] [review]
8/31	Proximal Policy Optimization Algorithms, J. Schulman et al, 2017.	Chris Ohk	[paper] [review]
8/31	Implementation Matters in Deep RL: A Case Study on PPO and TRPO, L. Engstrom et al, 2020.	Yunhyeok Kwak	[paper] [review]
9/7	Generative Adversarial Imitation Learning, J. Ho et al, 2016.	Hoesung Ryu	[paper] [review]
9/14	Efficient Reductions for Imitation Learning, S. Ross et al, 2010.	Hyecheol (Jerry) Jang	[paper] [review]
9/14	Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow, XB. Peng et al, 2018.	Do-Hoon Kim	[paper] [review]
9/14	Grandmaster Level in StarCraft II using Multi-agent Reinforcement Learning, O. Vinyals et al, 2019.	Donggu Kang	[paper] [review]

Study Member