Marcin Andrychowicz | DeepAI

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Lei Zhang
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Ilya Sutskever
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∙ 11/30/2021

Continuous Control With Ensemble Deep Deterministic Policy Gradients

The growth of deep reinforcement learning (RL) has brought multiple exci...

0 Piotr Januszewski, et al. ∙

∙ 08/16/2021

Implicitly Regularized RL with Implicit Q-Values

The Q-function is a central quantity in many Reinforcement Learning (RL)...

0 Nino Vieillard, et al. ∙

∙ 06/01/2021

What Matters for Adversarial Imitation Learning?

Adversarial imitation learning has become a popular framework for imitat...

0 Manu Orsini, et al. ∙

∙ 05/25/2021

Hyperparameter Selection for Imitation Learning

We address the issue of tuning hyperparameters (HPs) for imitation learn...

7 Léonard Hussenot, et al. ∙

∙ 06/10/2020

What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study

In recent years, on-policy reinforcement learning (RL) has been successf...

0 Marcin Andrychowicz, et al. ∙

∙ 10/16/2019

Solving Rubik's Cube with a Robot Hand

We demonstrate that models trained only in simulation can be used to sol...

9 OpenAI, et al. ∙

∙ 02/26/2018

Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

The purpose of this technical report is two-fold. First of all, it intro...

2 Matthias Plappert, et al. ∙

∙ 10/18/2017

Asymmetric Actor Critic for Image-Based Robot Learning

Deep reinforcement learning (RL) has proven a powerful technique in many...

0 Lerrel Pinto, et al. ∙

∙ 10/18/2017

Sim-to-Real Transfer of Robotic Control with Dynamics Randomization

Simulations are attractive environments for training agents as they prov...

0 Xue Bin Peng, et al. ∙

∙ 09/28/2017

Overcoming Exploration in Reinforcement Learning with Demonstrations

Exploration in environments with sparse rewards has been a persistent pr...

0 Ashvin Nair, et al. ∙

∙ 07/05/2017

Hindsight Experience Replay

Dealing with sparse rewards is one of the biggest challenges in Reinforc...

0 Marcin Andrychowicz, et al. ∙

∙ 06/06/2017

Parameter Space Noise for Exploration

Deep reinforcement learning (RL) methods generally engage in exploratory...

0 Matthias Plappert, et al. ∙

∙ 03/21/2017

One-Shot Imitation Learning

Imitation learning has been commonly applied to solve different tasks in...

0 Yan Duan, et al. ∙

∙ 06/14/2016

Learning to learn by gradient descent by gradient descent

The move from hand-designed features to learned features in machine lear...

0 Marcin Andrychowicz, et al. ∙

∙ 11/19/2015

Neural Random-Access Machines

In this paper, we propose and investigate a new neural network architect...

0 Karol Kurach, et al. ∙

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