ICML 2024 Workshop AutoRL Submissions

Snapshot Reinforcement Learning: Leveraging Prior Trajectories for Efficiency
Yanxiao Zhao, Yangge Qian, Tianyi Wang, Jingyang Shan, Xiaolin Qin
- Published: 17 Jun 2024, Last Modified: 20 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
Anthony Liang, Guy Tennenholtz, ChihWei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
- Published: 17 Jun 2024, Last Modified: 17 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning
Yifei Zhou, Hao Bai, Mert Cemri, Jiayi Pan, Alane Suhr, Sergey Levine, Aviral Kumar
- Published: 17 Jun 2024, Last Modified: 17 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone
Recursive Introspection: Teaching Foundation Model Agents How to Self-Improve
Yuxiao Qu, Tianjun Zhang, Naman Garg, Aviral Kumar
- Published: 17 Jun 2024, Last Modified: 01 Jul 2024
- AutoRL@ICML 2024
- Readers: Everyone
Can Learned Optimization Make Reinforcement Learning Less Difficult?
Alexander D. Goldie, Chris Lu, Matthew Thomas Jackson, Shimon Whiteson, Jakob Nicolaus Foerster
- Published: 17 Jun 2024, Last Modified: 28 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone
Higher Order and Self-Referential Evolution for Population-based Methods
Samuel Coward, Chris Lu, Alistair Letcher, Minqi Jiang, Jack Parker-Holder, Jakob Nicolaus Foerster
- Published: 17 Jun 2024, Last Modified: 01 Jul 2024
- AutoRL@ICML 2024
- Readers: Everyone
Conditional Meta-Reinforcement Learning with State Representation
Yuxuan Sun, Laura Toni, Yiannis Andreopoulos
- Published: 17 Jun 2024, Last Modified: 27 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone
XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Sergeevich Agarkov, Viacheslav Sinii, Sergey Kolesnikov
- Published: 17 Jun 2024, Last Modified: 25 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone
Universal benchmark for actuation dynamics adaptation in reinforcement learning
ICML 2024 Workshop AutoRL Submission2 Authors
- 17 May 2024 (modified: 17 Jun 2024)
- Submitted to AutoRL@ICML 2024
- Readers: Everyone
Distilling LLMs’ Decomposition Abilities into Compact Language Models
Denis Tarasov, Kumar Shridhar
- Published: 17 Jun 2024, Last Modified: 22 Jun 2024
- AutoRL@ICML 2024
- Readers: Everyone