12 papers · 1 filter
Accelerating Goal-Conditioned RL Algorithms and Research
MichaÅ Bortkiewicz, WÅadysÅaw PaÅucki, Vivek Myers +4
Self-supervision has the potential to transform reinforcement learning (RL), paralleling the breakthroughs it has enabled in other areas of machine learning. While self-supervised…
Training LLM Agents to Empower Humans
Evan Ellis, Vivek Myers, Jens Tuyls +3
Assistive agents should not only take actions on behalf of a human, but also step out of the way and cede control when there are important decisions to be made. However, current me…
Demystifying the Mechanisms Behind Emergent Exploration in Goal-conditioned RL
Mahsa Bastankhah, Grace Liu, Dilip Arumugam +2
In this work, we take a first step toward elucidating the mechanisms behind emergent exploration in unsupervised reinforcement learning. We study Single-Goal Contrastive Reinforcem…
Can a MISL Fly? Analysis and Ingredients for Mutual Information Skill Learning
Chongyi Zheng, Jens Tuyls, Joanne Peng +1
Self-supervised learning has the potential of lifting several of the key challenges in reinforcement learning today, such as exploration, representation learning, and reward design…
Contrastive Difference Predictive Coding
Chongyi Zheng, Ruslan Salakhutdinov, Benjamin Eysenbach
Predicting and reasoning about the future lie at the heart of many time-series questions. For example, goal-conditioned reinforcement learning can be viewed as learning representat…
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
Chongyi Zheng, Benjamin Eysenbach, Homer Walke +4
Robotic systems that rely primarily on self-supervised learning have the potential to decrease the amount of human annotation and engineering effort required to learn control strat…