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05/23/2022
Data augmentation for efficient learning from parametric experts
We present a simple, yet powerful data-augmentation technique to enable ...
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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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02/15/2022
NeuPL: Neural Population Learning
Learning in strategy games (e.g. StarCraft, poker) requires the discover...
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12/09/2021
Learning Transferable Motor Skills with Hierarchical Latent Mixture Policies
For robots operating in the real world, it is desirable to learn reusabl...
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12/03/2021
Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning
Artificial neural systems trained using reinforcement, supervised, and u...
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10/07/2021
Evaluating model-based planning and planner amortization for continuous control
There is a widespread intuition that model-based control methods should ...
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09/29/2021
Learning Dynamics Models for Model Predictive Agents
Model-Based Reinforcement Learning involves learning a dynamics model fr...
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05/25/2021
From Motor Control to Team Play in Simulated Humanoid Football
Intelligent behaviour in the physical world exhibits structure at multip...
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10/12/2020
Local Search for Policy Iteration in Continuous Control
We present an algorithm for local, regularized, policy improvement in re...
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09/30/2020
Learning to swim in potential flow
Fish swim by undulating their bodies. These propulsive motions require c...
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06/26/2020
Critic Regularized Regression
Offline reinforcement learning (RL), also known as batch RL, offers the ...
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06/24/2020
RL Unplugged: Benchmarks for Offline Reinforcement Learning
Offline methods for reinforcement learning have the potential to help br...
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06/22/2020
dm_control: Software and Tasks for Continuous Control
The dm_control software package is a collection of Python libraries and ...
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04/23/2020
Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning
Standard planners for sequential decision making (including Monte Carlo ...
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11/15/2019
Reusable neural skill embeddings for vision-guided whole body movement and object manipulation
Both in simulation settings and robotics, there is an ambition to produc...
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02/19/2019
Emergent Coordination Through Competition
We study the emergence of cooperative behaviors in reinforcement learnin...
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11/28/2018
Neural probabilistic motor primitives for humanoid control
We focus on the problem of learning a single motor module that can flexi...
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11/23/2018
Hierarchical visuomotor control of humanoids
We aim to build complex humanoid agents that integrate perception, motor...
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06/04/2018
Graph networks as learnable physics engines for inference and control
Understanding and interacting with everyday physical scenes requires ric...
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02/26/2018
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
We propose a model-free deep reinforcement learning method that leverage...
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01/02/2018
DeepMind Control Suite
The DeepMind Control Suite is a set of continuous control tasks with a s...
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07/07/2017
Emergence of Locomotion Behaviours in Rich Environments
The reinforcement learning paradigm allows, in principle, for complex be...
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11/13/2015
