Leonard Hasenclever | DeepAI

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∙ 07/18/2023

Towards A Unified Agent with Foundation Models

Language Models and Vision Language Models have recently demonstrated un...

0 Norman Di Palo, et al. ∙

∙ 06/14/2023

Language to Rewards for Robotic Skill Synthesis

Large language models (LLMs) have demonstrated exciting progress in acqu...

0 Wenhao Yu, et al. ∙

∙ 05/18/2023

A Generalist Dynamics Model for Control

We investigate the use of transformer sequence models as dynamics models...

0 Ingmar Schubert, et al. ∙

∙ 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 ...

0 Tuomas Haarnoja, et al. ∙

∙ 02/24/2023

Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains

In this paper we study the problem of learning multi-step dynamics predi...

0 Jingwei Zhang, et al. ∙

∙ 10/10/2022

NeRF2Real: Sim2real Transfer of Vision-guided Bipedal Motion Skills using Neural Radiance Fields

We present a system for applying sim2real approaches to "in the wild" sc...

0 Arunkumar Byravan, et al. ∙

∙ 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...

0 Steven Bohez, et al. ∙

∙ 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...

0 Dushyant Rao, et al. ∙

∙ 10/30/2021

Learning Coordinated Terrain-Adaptive Locomotion by Imitating a Centroidal Dynamics Planner

Dynamic quadruped locomotion over challenging terrains with precise foot...

5 Philemon Brakel, et al. ∙

∙ 10/07/2021

Evaluating model-based planning and planner amortization for continuous control

There is a widespread intuition that model-based control methods should ...

0 Arunkumar Byravan, et al. ∙

∙ 09/29/2021

Learning Dynamics Models for Model Predictive Agents

Model-Based Reinforcement Learning involves learning a dynamics model fr...

0 Michael Lutter, et al. ∙

∙ 05/25/2021

From Motor Control to Team Play in Simulated Humanoid Football

Intelligent behaviour in the physical world exhibits structure at multip...

2 Siqi Liu, et al. ∙

∙ 10/27/2020

Behavior Priors for Efficient Reinforcement Learning

As we deploy reinforcement learning agents to solve increasingly challen...

10 Dhruva Tirumala, et al. ∙

∙ 09/10/2020

Importance Weighted Policy Learning and Adaption

The ability to exploit prior experience to solve novel problems rapidly ...

6 Alexandre Galashov, et al. ∙

∙ 05/15/2020

A Distributional View on Multi-Objective Policy Optimization

Many real-world problems require trading off multiple competing objectiv...

0 Abbas Abdolmaleki, et al. ∙

∙ 04/23/2020

Divide-and-Conquer Monte Carlo Tree Search For Goal-Directed Planning

Standard planners for sequential decision making (including Monte Carlo ...

27 Giambattista Parascandolo, et al. ∙

∙ 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...

11 Josh Merel, et al. ∙

∙ 05/15/2019

Meta reinforcement learning as task inference

Humans achieve efficient learning by relying on prior knowledge about th...

5 Jan Humplik, et al. ∙

∙ 05/03/2019

Information asymmetry in KL-regularized RL

Many real world tasks exhibit rich structure that is repeated across dif...

6 Alexandre Galashov, et al. ∙

∙ 03/18/2019

Exploiting Hierarchy for Learning and Transfer in KL-regularized RL

As reinforcement learning agents are tasked with solving more challengin...

20 Dhruva Tirumala, et al. ∙

∙ 11/28/2018

Neural probabilistic motor primitives for humanoid control

We focus on the problem of learning a single motor module that can flexi...

12 Josh Merel, et al. ∙

∙ 06/05/2018

Mix&Match - Agent Curricula for Reinforcement Learning

We introduce Mix&Match (M&M) - a training framework designed to facilita...

2 Wojciech Marian Czarnecki, et al. ∙

∙ 03/15/2018

Sylvester Normalizing Flows for Variational Inference

Variational inference relies on flexible approximate posterior distribut...

0 Rianne van den Berg, et al. ∙

∙ 09/14/2016

Relativistic Monte Carlo

Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCM...

0 Xiaoyu Lu, et al. ∙

∙ 12/31/2015

Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server

This paper makes two contributions to Bayesian machine learning algorith...

0 Leonard Hasenclever, et al. ∙

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