rl-paper-study
Reinforcement Learning paper review study
파일 탐색기
- 230227 - LECO, Learnable Episodic Count for Task-Specific Intrinsic Reward, D. Jo et al, 2022.pdf
- 230306 - SUNRISE, A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning, K. Lee et al, 2020.pdf
- 230313 - Deep Reinforcement Learning that Matters, P. Henderson et al, 2017.pdf
- 230320 - Know Your Action Set, Learning Action Relations for Reinforcement Learning, A. Jain et al, 2022.pdf
- 230320 - Same State, Different Task, Continual Reinforcement Learning without Interference, S. Kessler et al, 2021.pdf
- 230327 - Aligning Text-to-Image Models using Human Feedback, K. Lee et al, 2023.pdf
- 230327 - Deep Reinforcement Learning from Human Preferences, P. Christiano et al, 2017.pdf
- 230403 - Human-Level Play in the Game of Diplomacy by Combining Language Models with Strategic Reasoning, Meta Fundamental AI Research Diplomacy Team, 2022.pdf
- 230403 - QMIX, Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning, T. Rashid et al, 2018.pdf
- 230410 - Hierarchically and Cooperatively Learning Traffic Signal Control, B. Xu et al, 2021.pdf
- 230410 - Stochastic Latent Actor-Critic, Deep Reinforcement Learning with a Latent Variable Model, AX. Lee et al, 2019.pdf
- 230417 - A Simple Neural Attentive Meta-Learner, N. Mishra et al, 2017.pdf
- 230417 - Dynamic Multi-Objective Scheduling for Flexible Job Shop by Deep Reinforcement Learning, S. Luo et al, 2021.pdf
- README.md
- README.md
- 200511 - Dueling Network Architectures for Deep Reinforcement Learning, Wang et al, 2015.pdf
- 200511 - Playing Atari with Deep Reinforcement Learning, Mnih et al, 2013.pdf
- 200525 - Asynchronous Methods for Deep Reinforcement Learning, Mnih et al, 2016.pdf
- 200525 - Deep Reinforcement Learning with Double Q-learning, Hasselt et al 2015.pdf
- 200601 - Continuous Control With Deep Reinforcement Learning, Lillicrap et al, 2015.pdf
- 200601 - Mastering the game of Go with deep neural networks and tree search, D. Silver et al, Nature, 2016.pdf
- 200608 - Curiosity-driven Exploration by Self-supervised Prediction, Pathak et al, 2017.pdf
- 200608 - Mastering the game of Go without human knowledge, D. Silver et al, Nature, 2017.pdf
- 200622 - Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model, J. Schrittwieser et al, 2019.pdf
- 200629 - Contextual Decision Processes with low Bellman rank are PAC-Learnable, N. Jiang et al, 2017.pdf
- 200629 - Evolution Strategies as a Scalable Alternative to Reinforcement Learning, Salimans et al, 2017.pdf
- 200629 - QT-Opt Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation, Kalashnikov et al, 2018.pdf
- README.md
- 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
- 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 - Program Guided Agent, SH. Sun et al, 2020.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 - Proximal Policy Optimization Algorithms, Schulman et al, 2017.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 - 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
- README.md
- 201109 - Trust Region Policy Optimization, Schulman et al, 2015.pdf
- 201116 - High-dimensional Continuous Control using Generalized Advantage Estimation, J. Schulman et al.pdf
- 201116 - Model based Reinforcement Learning for Atari, L. Kaiser et al, 2019.pdf
- 201123 - Rainbow Combining Improvements in Deep Reinforcement Learning, M. Hessel et al, 2017.pdf
- 201123 - The Option-critic Architecture, PL. Bacon et al, 2017.pdf
- 201130 - Prioritized Experience Replay, T. Schaul et al, 2015.pdf
- 201207 - Distributed Prioritized Experience Replay, D. Horgan et al, 2018.pdf
- 201207 - IMPALA Scalable Distributed Deep-RL with Importance Weighted Actor-learner Architectures, L. Espeholt et al, 2018.pdf
- 201214 - A Distributional Perspective on Reinforcement Learning, MG. Bellemare et al, 2017.pdf
- 201214 - Addressing Function Approximation Error in Actor-critic Methods, S. Fujimoto et al, 2018.pdf
- 201221 - Action-gap Phenomenon in Reinforcement Learning, A. Farahmand et al, 2011.pdf
- 201228 - Agent57 Outperforming the Atari Human Benchmark, Badia, A. P. et al, 2020.pdf
- README.md
- 210329 - Dueling Network Architectures for Deep Reinforcement Learning, Wang et al, 2015.pdf
- 210329 - Sim-to-Real Leaning of All Common Bipedal Gaits via Periodic Reward Composition, J. Siekmann et al, 2020.pdf
- 210405 - Asynchronous Methods for Deep Reinforcement Learning, Mnih et al, 2016.pdf
- 210412 - Adversarially Guided Actor-Critic, Y. Flet-Berliac et al, 2021.pdf
- 210412 - Hindsight Experience Replay, M. Andrychowicz et al, 2017.pdf
- 210419 - Addressing Function Approximation Error in Actor-Critic Methods, S. Fujimoto et al, 2018.pdf
- 210419 - Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments, R. Lowe et al, 2017.pdf
- 210426 - Generating Text with Deep Reinforcement Learning, H. Guo et al, 2015.pdf
- 210503 - Soft Actor-Critic Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, T. Haarnoja et al, 2018.pdf
- 210510 - Randomized Ensembled Double Q-Learning Learning Fast Without a Model, X. Chen et al, 2021.pdf
- 210517 - Continuous Control with Deep Reinforcement Learning, TP. Lillicrap et al, 2015.pdf
- 210517 - Efficient Hyperparameters Optimization Through Model-based Reinforcement Learning and Meta-Learning, J. Wu et al, 2020.pdf
- README.md
- 210705 - Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks, C. Finn et al, 2017.pdf
- 210705 - Multi-Agent Cooperation and the Emergence of (Natural) Language, A. Lazaridou et al, 2016.pdf
- 210712 - Learning a Contact-Adaptive Controller for Robust, Efficient Legged Locomotion, X. Da et al, 2020.pdf
- 210712 - Reinforcement Learning with Unsupervised Auxiliary Tasks, M. Jaderberg et al, 2016.pdf
- 210719 - Distributional Reinforcement Learning with Quantile Regression, W. Dabney et al, 2017.pdf
- 210726 - Combining Deep Reinforcement Learning and Search for Imperfect-Information Games, N. Brown et al, 2020.pdf
- 210726 - G-Learner and GIRL, Goal Based Wealth Management with Reinforcement Learning, M. Dixon et al, 2020.pdf
- 210802 - Evolving Reinforcement Learning Algorithms, JD. Co-Reyes et al, 2021.pdf
- 210802 - RL^2, Fast Reinforcement Learning via Slow Reinforcement Learning, Y. Duan et al, 2016.pdf
- 210809 - QMIX, Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning, T. Rashid et al, 2018.pdf
- 210816 - Proximal Policy Optimization Algorithms, J. Schulman et al, 2017.pdf
- 210823 - Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems, D. Gammelli et al, 2021.pdf
- 210823 - Soft Actor-Critic, Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, T. Haarnoja et al, 2018.pdf
- 210830 - Smooth Exploration for Robotic Reinforcement Learning, A. Raffin et al, 2021.pdf
- 210830 - Vector-based Navigation using Grid-like Representations in Artificial Agents, A. Banino et al, 2018.pdf
- README.md
- 211011 - Exploration by Random Network Distillation, Y. Bruda et al, 2018.pdf
- 211018 - Rainbow, Combining Improvements in Deep Reinforcement Learning, M. Hessel et al, 2017.pdf
- 211018 - Recommending Cryptocurrency Trading Points with Deep Reinforcement Learning Approach, O. Sattarov et al, 2020.pdf
- 211025 - Improving Sample Efficiency in Model-Free Reinforcement Learning from Images, D. Yarats et al, 2019.pdf
- 211025 - Mastering Visual Continuous Control, Improved Data-Augmented Reinforcement Learning, D. Yarats et al, 2021.pdf
- 211101 - BADGR, The Berkeley Autonomous Driving Ground Robot, G. Kahn et al, 2020.pdf
- 211101 - Curiosity-driven Exploration by Self-supervised Prediction, D. Pathak et al, 2017.pdf
- 211108 - A Graph Placement Methodology for Fast Chip Design, A. Mirhoseini et al, 2021.pdf
- 211108 - Neural Combinatorial Optimization with Reinforcement Learning, I. Bello et al, 2016.pdf
- 211115 - Deep Reinforcement Learning for Trading, Z. Zhang et al, 2019.pdf
- 211115 - Reinforcement Learning for Integer Programming, Learning to Cut, Y. Tang et al, 2019.pdf
- 211122 - Decision Transformer, Reinforcement Learning via Sequence Modeling, L. Chen et al, 2021.pdf
- 211122 - Reward is Enough, D. Silver et al, 2021.pdf
- 211129 - RMA, Rapid Motor Adaptation for Legged Robots, A. Kumar et al, 2021.pdf
- 211129 - Toward A Thousand Lights, Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control, C. Chen et al, 2020.pdf
- README.md
- 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
- 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 - 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 - 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 - Recent Advances in Reinforcement Learning in Finance, B. Hambly et al, 2021.pdf
- 220314 - Phasic Policy Gradient, K. Cobbe et al, 2020.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
- 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 - Return-based Scaling, Yet Another Normalisation Trick for Deep RL, T. Schaul et al, 2021.pdf
- README.md
- 220523 - A Reinforcement Learning Algorithm for The 2D-rectangular Strip Packing Problem, X. Zhao et al, 2022.pdf
- 220530 - Explainable Reinforcement Learning, A Survey, E. Puiutta et al, 2020.pdf
- 220530 - Implicit Distributional Reinforcement Learning, Y. Yue et al, 2020.pdf
- 220613 - Offline Reinforcement Learning as One Big Sequence Modeling Problem, M. Janner et al, 2021.pdf
- 220613 - Optimization of Global Production Scheduling with Deep Reinforcement Learning, B. Waschneck et al, 2018.pdf
- 220620 - On Learning Intrinsic Rewards for Policy Gradient Methods, Z. Zheng et al, 2018.pdf
- 220627 - Battlesnake Challenge, A Multi-agent Reinforcement Learning Playground with Human-in-the-loop.pdf
- 220627 - Molecular De-novo Design through Deep Reinforcement Learning, M. Olivecrona et al, 2017.pdf
- 220704 - Magnetic Control of Tokamak Plasmas through Deep Reinforcement Learning, J. Degrave et al, 2022.pdf
- 220704 - Sub-policy Adaptation for Hierarchical Reinforcement Learning.pdf
- 220711 - A Generalist Agent, S. Reed et al, 2022.pdf
- 220711 - Leveraging Procedural Generation to Benchmark Reinforcement Learning, K. Cobbe et al, 2019.pdf
- 220718 - Implementation of IPDALight, Intensity- and Phase Duration-aware Traffic Signal Control based on Reinforcement Learning, W. Zhao et al, 2021.pdf
- 220718 - The Artificial Intelligence Clinician Learns Optimal Treatment Strategies for Sepsis in Intensive Care, M. Komorowski et al, 2018.pdf
- 220725 - Implementation of Addressing Function Approximation Error in Actor-Critic Methods, S. Fujimoto et al, 2018.pdf
- 220725 - Language Understanding for Text-based Games Using Deep Reinforcement Learning, K. Narasimhan et al, 2015.pdf
- README.md
- 221024 - Parameterized MDPs and Reinforcement Learning Problems -- A Maximum Entropy Principle Based Framework, A. Srivastava et al, 2020.pdf
- 221024 - Selective Token Generation for Few-shot Natural Language Generation, D. Jo et al, 2022.pdf
- 221031 - Decision Transformer, Reinforcement Learning via Sequence Modeling, L. Chen et al, 2021.pdf
- 221031 - Planning with Diffusion for Flexible Behavior Synthesis, M. Janner et al, 2022.pdf
- 221107 - Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning, Z. Wang et al, 2022.pdf
- 221107 - The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games, C. Yu et al, 2021.pdf
- 221114 - Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Reward, K. Zhou et al, 2017.pdf
- 221121 - Hindsight Credit Assignment, A. Harutyunyan et al, 2019.pdf
- 221121 - Never Give Up, Learning Directed Exploration Strategies, AP. Badia et al, 2019.pdf
- 221128 - Learning Improvement Heuristics for Solving Routing Problems, Y. Wu et al, 2019.pdf
- 221128 - Mastering the Game of Stratego with Model-Free Multiagent Reinforcement Learning, J. Perolat et al, 2022.pdf
- 221205 - Hierarchical Reinforcement Learning for Air-to-Air Combat, AP. Pope et al, 2021.pdf
- 221212 - A Review of Reinforcement Learning Based Intelligent Optimization for Manufacturing Scheduling, L. Wang et al, 2021.pdf
- 221212 - Is Conditional Generative Modeling all you need for Decision-Making, A. Ajay et al, 2022.pdf
- 221212 - When to Trust Your Model, Model-Based Policy Optimization, M. Janner et al, 2019.pdf
- README.md
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