rl-paper-study/7th at main · utilForever/rl-paper-study · GitHub

Name		Name	Last commit message	Last commit date
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220207 - Maximum a Posteriori Policy Optimisation, A. Abdolmalek et al, 2018.pdf		220207 - Maximum a Posteriori Policy Optimisation, A. Abdolmalek et al, 2018.pdf
220214 - On the Expressivity of Markov Reward, D. Abel et al, 2021.pdf		220214 - On the Expressivity of Markov Reward, D. Abel et al, 2021.pdf
220221 - Batch Size-invariance for Policy Optimization, J. Hilton et al, 2022.pdf		220221 - Batch Size-invariance for Policy Optimization, J. Hilton et al, 2022.pdf
220221 - Playing Atari with Deep Reinforcement Learning, V. Mnih et al, 2013.pdf		220221 - Playing Atari with Deep Reinforcement Learning, V. Mnih et al, 2013.pdf
220221 - Policies Modulating Trajectory Generators, A. Iscen et al, 2019.pdf		220221 - Policies Modulating Trajectory Generators, A. Iscen et al, 2019.pdf
220228 - Automated Reinforcement Learning (AutoRL), A Survey and Open Problems, J. Parker-Holder et al, 2022.pdf		220228 - Automated Reinforcement Learning (AutoRL), A Survey and Open Problems, J. Parker-Holder et al, 2022.pdf
220228 - IPDALight, Intensity- and phase duration-aware traffic signal control based on Reinforcement Learning, W. Zhao et al, 2021.pdf		220228 - IPDALight, Intensity- and phase duration-aware traffic signal control based on Reinforcement Learning, W. Zhao et al, 2021.pdf
220307 - Parametrized Deep Q-Network Learning, RL with Discrete-Continuous Hybrid Action Space, J. Xiong et al, 2018.pdf		220307 - Parametrized Deep Q-Network Learning, RL with Discrete-Continuous Hybrid Action Space, J. Xiong et al, 2018.pdf
220307 - Recent Advances in Reinforcement Learning in Finance, B. Hambly et al, 2021.pdf		220307 - Recent Advances in Reinforcement Learning in Finance, B. Hambly et al, 2021.pdf
220314 - Phasic Policy Gradient, K. Cobbe et al, 2020.pdf		220314 - Phasic Policy Gradient, K. Cobbe et al, 2020.pdf
220314 - Reverb, A Framework For Experience Replay, A. Cassirer et al, 2021.pdf		220314 - Reverb, A Framework For Experience Replay, A. Cassirer et al, 2021.pdf
220321 - A Minimalist Approach to Offline Reinforcement Learning, S. Fujimoto et al, 2021.pdf		220321 - A Minimalist Approach to Offline Reinforcement Learning, S. Fujimoto et al, 2021.pdf
220328 - Generative Design by Using Exploration Approaches of Reinforcement Learning in Density-Based Structural Topology Optimization, H. Sun et al, 2020.pdf		220328 - Generative Design by Using Exploration Approaches of Reinforcement Learning in Density-Based Structural Topology Optimization, H. Sun et al, 2020.pdf
220328 - Playtesting in Match 3 Game Using Strategic Plays via Reinforcement Learning, Y. Shin et al, 2020.pdf		220328 - Playtesting in Match 3 Game Using Strategic Plays via Reinforcement Learning, Y. Shin et al, 2020.pdf
220328 - Return-based Scaling, Yet Another Normalisation Trick for Deep RL, T. Schaul et al, 2021.pdf		220328 - Return-based Scaling, Yet Another Normalisation Trick for Deep RL, T. Schaul et al, 2021.pdf
README.md		README.md

README.md

7th Study Paper List

Date	Paper	Presenter	Links
2/7	Diversity is All You Need: Learning Skills without a Reward Function, B. Eysenbach et al, 2018.	Mark Young	[paper] [review]
2/7	Maximum a Posteriori Policy Optimisation, A. Abdolmalek et al, 2018.	Daejin Jo	[paper] [review]
2/14	On the Expressivity of Markov Reward, D. Abel et al, 2021.	Bumjin Park	[paper] [review]
2/21	Batch Size-invariance for Policy Optimization, J. Hilton et al, 2022.	Chris Ohk	[paper] [review]
2/21	Policies Modulating Trajectory Generators, A. Iscen et al, 2019.	Hansol Kang	[paper] [review]
2/21	Playing Atari with Deep Reinforcement Learning, V. Mnih et al, 2013.	Jinsu Kim	[paper] [review]
2/28	Automated Reinforcement Learning (AutoRL): A Survey and Open Problems, J. Parker-Holder et al, 2022.	Donggu Kang	[paper] [review]
2/28	IPDALight: Intensity- and phase duration-aware traffic signal control based on Reinforcement Learning, W. Zhao et al, 2021.	Jiho Yeo	[paper] [review]
3/7	Recent Advances in Reinforcement Learning in Finance, B. Hambly et al, 2021.	Taejun Park	[paper] [review]
3/7	Parametrized Deep Q-Network Learning: RL with Discrete-Continuous Hybrid Action Space, J. Xiong et al, 2018.	Seungeon Baek	[paper] [review]
3/14	Reverb: A Framework For Experience Replay, A. Cassirer et al, 2021.	Dokyoon Yoon	[paper] [review]
3/14	Phasic Policy Gradient, K. Cobbe et al, 2020.	Sungkwon On	[paper] [review]
3/21	A Minimalist Approach to Offline Reinforcement Learning, S. Fujimoto et al, 2021.	Hyeonhoon Lee	[paper] [review]
3/28	Generative Design by Using Exploration Approaches of Reinforcement Learning in Density-Based Structural Topology Optimization, H. Sun et al, 2020.	Hyogeun Park	[paper] [review]
3/28	Playtesting in Match 3 Game Using Strategic Plays via Reinforcement Learning, Y. Shin et al, 2020.	Younkyung Jang	[paper] [review]
3/28	Return-based Scaling: Yet Another Normalisation Trick for Deep RL, T. Schaul et al, 2021.	Bongseok Kim	[paper] [review]

Study Member