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06/02/2023
SACSoN: Scalable Autonomous Data Collection for Social Navigation
Machine learning provides a powerful tool for building socially complian...
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04/20/2023
IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies
Effective offline RL methods require properly handling out-of-distributi...
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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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03/03/2023
Learning to Influence Human Behavior with Offline Reinforcement Learning
In the real world, some of the most complex settings for learned agents ...
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02/19/2023
Robust and Versatile Bipedal Jumping Control through Multi-Task Reinforcement Learning
This work aims to push the limits of agility for bipedal robots by enabl...
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12/21/2022
Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios
Imitation learning (IL) is a simple and powerful way to use high-quality...
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12/16/2022
Offline Reinforcement Learning for Visual Navigation
Reinforcement learning can enable robots to navigate to distant goals wh...
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10/24/2022
FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners
Large language models (LLM) trained using the next-token-prediction obje...
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10/07/2022
GNM: A General Navigation Model to Drive Any Robot
Learning provides a powerful tool for vision-based navigation, but the c...
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08/16/2022
A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning
Deep reinforcement learning is a promising approach to learning policies...
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05/27/2022
Multimodal Masked Autoencoders Learn Transferable Representations
Building scalable models to learn from diverse, multimodal data remains ...
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05/04/2022
ASE: Large-Scale Reusable Adversarial Skill Embeddings for Physically Simulated Characters
The incredible feats of athleticism demonstrated by humans are made poss...
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04/18/2022
CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning
Conventionally, generation of natural language for dialogue agents may b...
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02/04/2022
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning
In this paper, we study the problem of enabling a vision-based robotic m...
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06/24/2021
Multi-Robot Deep Reinforcement Learning for Mobile Navigation
Deep reinforcement learning algorithms require large and diverse dataset...
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04/16/2021
MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale
General-purpose robotic systems must master a large repertoire of divers...
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04/12/2021
RECON: Rapid Exploration for Open-World Navigation with Latent Goal Models
We describe a robotic learning system for autonomous navigation in diver...
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12/17/2020
ViNG: Learning Open-World Navigation with Visual Goals
We propose a learning-based navigation system for reaching visually indi...
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12/14/2020
WILDS: A Benchmark of in-the-Wild Distribution Shifts
Distribution shifts can cause significant degradation in a broad range o...
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05/27/2020
MOPO: Model-based Offline Policy Optimization
Offline reinforcement learning (RL) refers to the problem of learning po...
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04/15/2020
D4RL: Datasets for Deep Data-Driven Reinforcement Learning
The offline reinforcement learning (RL) problem, also referred to as bat...
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04/02/2020
Learning Agile Robotic Locomotion Skills by Imitating Animals
Reproducing the diverse and agile locomotion skills of animals has been ...
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03/18/2020
Sequential Forecasting of 100,000 Points
Predicting the future is a crucial first step to effective control, sinc...
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12/11/2019
SMiRL: Surprise Minimizing RL in Dynamic Environments
All living organisms struggle against the forces of nature to carve out ...
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10/24/2019
RoboNet: Large-Scale Multi-Robot Learning
Robot learning has emerged as a promising tool for taming the complexity...
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07/01/2019
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model
Deep reinforcement learning (RL) algorithms can use high-capacity deep n...
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06/12/2019
Efficient Exploration via State Marginal Matching
To solve tasks with sparse rewards, reinforcement learning algorithms mu...
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05/31/2019
Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations
Reinforcement learning (RL) for robotics is challenging due to the diffi...
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05/27/2019
SQIL: Imitation Learning via Regularized Behavioral Cloning
Learning to imitate expert behavior given action demonstrations containi...
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03/08/2019
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning
In standard reinforcement learning, each new skill requires a manually-d...
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03/04/2019
VideoFlow: A Flow-Based Generative Model for Video
Generative models that can model and predict sequences of future events ...
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01/11/2019
Low Level Control of a Quadrotor with Deep Model-Based Reinforcement learning
Generating low-level robot controllers often requires manual parameters ...
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12/26/2018
Learning to Walk via Deep Reinforcement Learning
Deep reinforcement learning suggests the promise of fully automated lear...
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12/18/2018
Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks
Real world data, especially in the domain of robotics, is notoriously co...
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12/13/2018
Soft Actor-Critic Algorithms and Applications
Model-free deep reinforcement learning (RL) algorithms have been success...
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10/02/2018
EMI: Exploration with Mutual Information Maximizing State and Action Embeddings
Policy optimization struggles when the reward feedback signal is very sp...
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04/08/2018
DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills
A longstanding goal in character animation is to combine data-driven spe...
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03/30/2018
Learning to Adapt: Meta-Learning for Model-Based Control
Although reinforcement learning methods can achieve impressive results i...
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02/16/2018
Diversity is All You Need: Learning Skills without a Reward Function
Intelligent creatures can explore their environments and learn useful sk...
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02/06/2018
Shared Autonomy via Deep Reinforcement Learning
In shared autonomy, user input is combined with semi-autonomous control ...
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11/14/2017
Neural Network Dynamics Models for Control of Under-actuated Legged Millirobots
Millirobots are a promising robotic platform for many applications due t...
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07/10/2017
Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration
In this paper, we propose a multi-task learning from demonstration metho...
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03/01/2016
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization
Reinforcement learning can acquire complex behaviors from high-level spe...
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02/09/2016
Value Iteration Networks
We introduce the value iteration network (VIN): a fully differentiable n...
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04/02/2015
