384 citations · 1.5k across the 50 of their papers we have counts for
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The Surprising Effectiveness of Representation Learning for Visual Imitation
Jyothish Pari, Nur Muhammad Shafiullah, Sridhar Pandian Arunachalam +1
While visual imitation learning offers one of the most effective ways of learning from visual demonstrations, generalizing from them requires either hundreds of diverse demonstrati…
URLB: Unsupervised Reinforcement Learning Benchmark
Michael Laskin, Denis Yarats, Hao Liu +6
Deep Reinforcement Learning (RL) has emerged as a powerful paradigm to solve a range of complex yet specific control tasks. Yet training generalist agents that can quickly adapt to…
Mastering Visual Continuous Control: Improved Data-Augmented Reinforcement Learning
Denis Yarats, Rob Fergus, Alessandro Lazaric +1
We present DrQ-v2, a model-free reinforcement learning (RL) algorithm for visual continuous control. DrQ-v2 builds on DrQ, an off-policy actor-critic approach that uses data augmen…
Playful Interactions for Representation Learning
Sarah Young, Jyothish Pari, Pieter Abbeel +1
One of the key challenges in visual imitation learning is collecting large amounts of expert demonstrations for a given task. While methods for collecting human demonstrations are…
GEM: Group Enhanced Model for Learning Dynamical Control Systems
Philippe Hansen-Estruch, Wenling Shang, Lerrel Pinto +2
Learning the dynamics of a physical system wherein an autonomous agent operates is an important task. Often these systems present apparent geometric structures. For instance, the t…
Simultaneous Navigation and Construction Benchmarking Environments
Wenyu Han, Chen Feng, Haoran Wu +5
We need intelligent robots for mobile construction, the process of navigating in an environment and modifying its structure according to a geometric design. In this task, a major r…