Dhruva Tirumala | DeepAI

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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 ...

0 Tuomas Haarnoja, et al. ∙

∙ 11/24/2022

SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration

The ability to effectively reuse prior knowledge is a key requirement wh...

0 Giulia Vezzani, et al. ∙

∙ 09/05/2022

MO2: Model-Based Offline Options

The ability to discover useful behaviours from past experience and trans...

0 Sasha Salter, 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. ∙

∙ 10/08/2021

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Strategic diversity is often essential in games: in multi-player games, ...

0 Marta Garnelo, 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. ∙

∙ 07/30/2020

Data-efficient Hindsight Off-policy Option Learning

Solutions to most complex tasks can be decomposed into simpler, intermed...

38 Markus Wulfmeier, et al. ∙

∙ 09/26/2019

V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control

Some of the most successful applications of deep reinforcement learning ...

0 H. Francis Song, 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. ∙

∙ 11/23/2018

Hierarchical visuomotor control of humanoids

We aim to build complex humanoid agents that integrate perception, motor...

0 Josh Merel, et al. ∙

∙ 09/26/2017

Flexible Support for Fast Parallel Commutative Updates

Privatizing data is a useful strategy for increasing parallelism in a sh...

0 Vignesh Balaji, et al. ∙

∙ 11/17/2016

Learning to reinforcement learn

In recent years deep reinforcement learning (RL) systems have attained s...

0 Jane X Wang, et al. ∙

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