18 citations · 31 across the 6 of their papers we have counts for
6 papers
What Does It Take For A Generalist Robot Policy To Adapt Using Minimal Data?
Shreyas Kowshik, Sreyas Venkataraman, Leo Wang +3
A central goal in robot learning is to move beyond task-specific human data collection toward robots that improve through autonomous interaction. Yet fully autonomous learning rema…
FADA: Few-Shot Domain Adaptation via Dynamics Alignment for Humanoid Control
Angchen Xie, Nikhil Sobanbabu, Ishayu Shikhare +3
High-precision humanoid control is limited by target-domain dynamics mismatch, where the same control objective can induce different realized motions under changes in terrain, payl…
Turning Video Models into Generalist Robot Policies
Sizhe Lester Li, Evan Kim, Xingjian Bai +4
Video generative models have emerged as a promising robotics backbone, capable of generating videos that depict the completion of complex tasks across embodiments and environments.…
Exploration and Incentives in Reinforcement Learning
Max Simchowitz, Aleksandrs Slivkins
How do you incentivize self-interested agents to when they prefer to ? We consider complex exploration problems, where each agent faces the sam…
Constrained episodic reinforcement learning in concave-convex and knapsack settings
Kianté Brantley, Miroslav Dudik, Thodoris Lykouris +4
We propose an algorithm for tabular episodic reinforcement learning with constraints. We provide a modular analysis with strong theoretical guarantees for settings with concave rew…
Corruption-robust exploration in episodic reinforcement learning
Thodoris Lykouris, Max Simchowitz, Aleksandrs Slivkins +1
We initiate the study of multi-stage episodic reinforcement learning under adversarial corruptions in both the rewards and the transition probabilities of the underlying system ext…