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07/24/2023
Contrastive Example-Based Control
While many real-world problems that might benefit from reinforcement lea...
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07/24/2023
A Connection between One-Step Regularization and Critic Regularization in Reinforcement Learning
As with any machine learning problem with limited data, effective offlin...
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07/22/2023
HIQL: Offline Goal-Conditioned RL with Latent States as Actions
Unsupervised pre-training has recently become the bedrock for computer v...
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07/07/2023
When Do Transformers Shine in RL? Decoupling Memory from Credit Assignment
Reinforcement learning (RL) algorithms face two distinct challenges: lea...
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06/06/2023
Stabilizing Contrastive RL: Techniques for Offline Goal Reaching
In the same way that the computer vision (CV) and natural language proce...
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02/06/2023
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts
Training machine learning models robust to distribution shifts is critic...
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12/08/2022
Learning Options via Compression
Identifying statistical regularities in solutions to some tasks in multi...
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11/03/2022
Contrastive Value Learning: Implicit Models for Simple Offline RL
Model-based reinforcement learning (RL) methods are appealing in the off...
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09/18/2022
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective
While reinforcement learning (RL) methods that learn an internal model o...
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06/15/2022
Contrastive Learning as Goal-Conditioned Reinforcement Learning
In reinforcement learning (RL), it is easier to solve a task if given a ...
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06/07/2022
Imitating Past Successes can be Very Suboptimal
Prior work has proposed a simple strategy for reinforcement learning (RL...
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06/03/2022
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions
Supervised learning methods trained with maximum likelihood objectives o...
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12/20/2021
RvS: What is Essential for Offline RL via Supervised Learning?
Recent work has shown that supervised learning alone, without temporal d...
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10/22/2021
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks
Goal-conditioned reinforcement learning (RL) can solve tasks in a wide r...
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10/11/2021
Recurrent Model-Free RL is a Strong Baseline for Many POMDPs
Many problems in RL, such as meta RL, robust RL, and generalization in R...
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10/06/2021
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL
Many model-based reinforcement learning (RL) methods follow a similar te...
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10/06/2021
The Information Geometry of Unsupervised Reinforcement Learning
How can a reinforcement learning (RL) agent prepare to solve downstream ...
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09/07/2021
Robust Predictable Control
Many of the challenges facing today's reinforcement learning (RL) algori...
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04/15/2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills
We consider the problem of learning useful robotic skills from previousl...
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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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03/23/2021
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification
In the standard Markov decision process formalism, users specify tasks b...
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03/10/2021
Maximum Entropy RL (Provably) Solves Some Robust RL Problems
Many potential applications of reinforcement learning (RL) require guara...
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12/30/2020
Model-Based Visual Planning with Self-Supervised Functional Distances
A generalist robot must be able to complete a variety of tasks in its en...
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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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11/17/2020
C-Learning: Learning to Achieve Goals via Recursive Classification
We study the problem of predicting and controlling the future state dist...
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11/09/2020
f-IRL: Inverse Reinforcement Learning via State Marginal Matching
Imitation learning is well-suited for robotic tasks where it is difficul...
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10/27/2020
Learning to be Safe: Deep RL with a Safety Critic
Safety is an essential component for deploying reinforcement learning (R...
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08/14/2020
Interactive Visualization for Debugging RL
Visualization tools for supervised learning allow users to interpret, in...
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06/24/2020
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers
We propose a simple, practical, and intuitive approach for domain adapta...
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04/06/2020
Weakly-Supervised Reinforcement Learning for Controllable Behavior
Reinforcement learning (RL) is a powerful framework for learning to take...
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02/25/2020
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement
Multi-task reinforcement learning (RL) aims to simultaneously learn poli...
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12/12/2019
Learning To Reach Goals Without Reinforcement Learning
Imitation learning algorithms provide a simple and straightforward appro...
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10/04/2019
If MaxEnt RL is the Answer, What is the Question?
Experimentally, it has been observed that humans and animals often make ...
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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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06/12/2019
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
The history of learning for control has been an exciting back and forth ...
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06/12/2018
Unsupervised Meta-Learning for Reinforcement Learning
Meta-learning is a powerful tool that builds on multi-task learning to l...
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06/07/2018
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings
In this work, we take a representation learning perspective on hierarchi...
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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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11/18/2017
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning
Deep reinforcement learning algorithms can learn complex behavioral skil...
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12/04/2016
