Summary of Reinforcement Learning with Euclidean Data Augmentation For State-based Continuous Control, by Jinzhu Luo et al.
Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Controlby Jinzhu Luo, Dingyang Chen, Qi…
Summary of Generative Reward Models, by Dakota Mahan et al.
Generative Reward Modelsby Dakota Mahan, Duy Van Phung, Rafael Rafailov, Chase Blagden, Nathan Lile, Louis…
Summary of Neural-based Control For Cubesat Docking Maneuvers, by Matteo Stoisa et al.
Neural-based Control for CubeSat Docking Maneuversby Matteo Stoisa, Federica Paganelli Azza, Luca Romanelli, Mattia VarileFirst…
Summary of Sac-glam: Improving Online Rl For Llm Agents with Soft Actor-critic and Hindsight Relabeling, by Loris Gaven et al.
SAC-GLAM: Improving Online RL for LLM agents with Soft Actor-Critic and Hindsight Relabelingby Loris Gaven,…
Summary of Off-dynamics Conditional Diffusion Planners, by Wen Zheng Terence Ng et al.
Off-dynamics Conditional Diffusion Plannersby Wen Zheng Terence Ng, Jianda Chen, Tianwei ZhangFirst submitted to arxiv…
Summary of Dual Action Policy For Robust Sim-to-real Reinforcement Learning, by Ng Wen Zheng Terence et al.
Dual Action Policy for Robust Sim-to-Real Reinforcement Learningby Ng Wen Zheng Terence, Chen JiandaFirst submitted…
Summary of When to Trust Your Data: Enhancing Dyna-style Model-based Reinforcement Learning with Data Filter, by Yansong Li et al.
When to Trust Your Data: Enhancing Dyna-Style Model-Based Reinforcement Learning With Data Filterby Yansong Li,…
Summary of Mitigating Suboptimality Of Deterministic Policy Gradients in Complex Q-functions, by Ayush Jain et al.
Mitigating Suboptimality of Deterministic Policy Gradients in Complex Q-functionsby Ayush Jain, Norio Kosaka, Xinhu Li,…
Summary of Improve Value Estimation Of Q Function and Reshape Reward with Monte Carlo Tree Search, by Jiamian Li
Improve Value Estimation of Q Function and Reshape Reward with Monte Carlo Tree Searchby Jiamian…
Summary of Blendrl: a Framework For Merging Symbolic and Neural Policy Learning, by Hikaru Shindo et al.
BlendRL: A Framework for Merging Symbolic and Neural Policy Learningby Hikaru Shindo, Quentin Delfosse, Devendra…