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09/18/2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
In this work, we present a scalable reinforcement learning method for tr...
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08/24/2023
BridgeData V2: A Dataset for Robot Learning at Scale
We introduce BridgeData V2, a large and diverse dataset of robotic manip...
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07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
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03/06/2023
PaLM-E: An Embodied Multimodal Language Model
Large language models excel at a wide range of complex tasks. However, e...
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03/02/2023
Open-World Object Manipulation using Pre-trained Vision-Language Models
For robots to follow instructions from people, they must be able to conn...
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12/13/2022
RT-1: Robotics Transformer for Real-World Control at Scale
By transferring knowledge from large, diverse, task-agnostic datasets, m...
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11/02/2022
Dual Generator Offline Reinforcement Learning
In offline RL, constraining the learned policy to remain close to the da...
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11/02/2022
Offline RL With Realistic Datasets: Heteroskedasticity and Support Constraints
Offline reinforcement learning (RL) learns policies entirely from static...
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10/06/2022
A Real2Sim2Real Method for Robust Object Grasping with Neural Surface Reconstruction
Recent 3D-based manipulation methods either directly predict the grasp p...
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01/04/2021
Machine Learning for Robotic Manipulation
The past decade has witnessed the tremendous successes of machine learni...
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02/16/2020
First Order Optimization in Policy Space for Constrained Deep Reinforcement Learning
In reinforcement learning, an agent attempts to learn high-performing be...
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10/28/2019
Better Exploration with Optimistic Actor-Critic
Actor-critic methods, a type of model-free Reinforcement Learning, have ...
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10/05/2019
Towards Simplicity in Deep Reinforcement Learning: Streamlined Off-Policy Learning
The field of Deep Reinforcement Learning (DRL) has recently seen a surge...
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09/25/2019
Pre-training as Batch Meta Reinforcement Learning with tiMe
Pre-training is transformative in supervised learning: a large network t...
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03/28/2019