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05/24/2023
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Animals have evolved various agile locomotion strategies, such as sprint...
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04/26/2023
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning
We investigate whether Deep Reinforcement Learning (Deep RL) is able to ...
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11/24/2022
SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration
The ability to effectively reuse prior knowledge is a key requirement wh...
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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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09/17/2021
Is Curiosity All You Need? On the Utility of Emergent Behaviours from Curious Exploration
Curiosity-based reward schemes can present powerful exploration mechanis...
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08/23/2021
Collect Infer – a fresh look at data-efficient Reinforcement Learning
This position paper proposes a fresh look at Reinforcement Learning (RL)...
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11/03/2020
Representation Matters: Improving Perception and Exploration for Robotics
Projecting high-dimensional environment observations into lower-dimensio...
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10/29/2020
"What, not how": Solving an under-actuated insertion task from scratch
Robot manipulation requires a complex set of skills that need to be care...
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08/06/2020
Towards General and Autonomous Learning of Core Skills: A Case Study in Locomotion
Modern Reinforcement Learning (RL) algorithms promise to solve difficult...
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07/30/2020
Data-efficient Hindsight Off-policy Option Learning
Solutions to most complex tasks can be decomposed into simpler, intermed...
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05/15/2020
Simple Sensor Intentions for Exploration
Modern reinforcement learning algorithms can learn solutions to increasi...
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02/19/2020
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning
Off-policy reinforcement learning algorithms promise to be applicable in...
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01/02/2020
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics
Many real-world control problems involve both discrete decision variable...
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10/09/2019
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
Humans are masters at quickly learning many complex tasks, relying on an...
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06/26/2019
Regularized Hierarchical Policies for Compositional Transfer in Robotics
The successful application of flexible, general learning algorithms -- s...
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02/13/2019
Simultaneously Learning Vision and Feature-based Control Policies for Real-world Ball-in-a-Cup
We present a method for fast training of vision based control policies o...
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02/28/2018
Learning by Playing - Solving Sparse Reward Tasks from Scratch
We propose Scheduled Auxiliary Control (SAC-X), a new learning paradigm ...
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05/27/2017