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06/20/2023
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation
The ability to leverage heterogeneous robotic experience from different ...
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05/18/2023
A Generalist Dynamics Model for Control
We investigate the use of transformer sequence models as dynamics models...
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03/07/2023
Structured State Space Models for In-Context Reinforcement Learning
Structured state space sequence (S4) models have recently achieved state...
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10/25/2022
In-context Reinforcement Learning with Algorithm Distillation
We propose Algorithm Distillation (AD), a method for distilling reinforc...
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05/12/2022
A Generalist Agent
Inspired by progress in large-scale language modeling, we apply a simila...
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03/31/2022
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors
We investigate the use of prior knowledge of human and animal movement t...
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10/20/2021
Shaking the foundations: delusions in sequence models for interaction and control
The recent phenomenal success of language models has reinvigorated machi...
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04/04/2021
Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation
Many real-world applications such as robotics provide hard constraints o...
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02/20/2021
On Proximal Policy Optimization's Heavy-tailed Gradients
Modern policy gradient algorithms, notably Proximal Policy Optimization ...
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10/13/2019
Stabilizing Transformers for Reinforcement Learning
Owing to their ability to both effectively integrate information over lo...
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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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03/07/2019
Concurrent Meta Reinforcement Learning
State-of-the-art meta reinforcement learning algorithms typically assume...
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02/01/2019
The Hanabi Challenge: A New Frontier for AI Research
From the early days of computing, games have been important testbeds for...
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06/17/2018
Gated Path Planning Networks
Value Iteration Networks (VINs) are effective differentiable path planni...
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02/19/2018
Global Pose Estimation with an Attention-based Recurrent Network
The ability for an agent to localize itself within an environment is cru...
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01/24/2018
Active Neural Localization
Localization is the problem of estimating the location of an autonomous ...
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11/06/2016
Neuro-Symbolic Program Synthesis
Recent years have seen the proposal of a number of neural architectures ...
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11/09/2015
