Ashvin Nair und Reinforcement Learning - Info zur Person

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Alignment Newsletter #23 - LessWrong

www.lesswrong.com

Highlights. Visual Reinforcement Learning with Imagined Goals (Vitchyr Pong and Ashvin Nair): This is a blog post explaining a paper by the ...

[ ] Overcoming Exploration in Reinforcement Learning with...

arxiv.org

Submission history. From: Ashvin Nair [view email] [v1] Thu, 28 Sep :51:48 UTC (1,246 KB) [v2] Sun, 25 Feb :48:19 UTC (1,864 KB).

[ ] Residual Reinforcement Learning for Robot Control

arxiv.org

From: Ashvin Nair [view email] [v1] Fri, 7 Dec :10:23 UTC (3,136 KB) [v2] Tue, 18 Dec :40:20 UTC (3,204 KB). Full-text links: ...

[ ] Visual Reinforcement Learning with Imagined Goals

arxiv.org

Authors:Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin, Sergey Levine. (Submitted on 12 Jul (v1), last revised 4 Dec ...

Deep Reinforcement Learning for Industrial Insertion Tasks with ...

openreview.net

Gerrit Schoettler, Ashvin Nair, Jianlan Luo, Shikhar Bahl, Juan Aparicio Ojea, Eugen Solowjow, Sergey Levine. 07 May 2019ICML Workshop RL4RealLife ...

Ashvin Nair · SlidesLive

slideslive.com

by; Aaron Havens,; Abhishek Gupta, … 488 views; Dec 14, :00:00. Deep Reinforcement Learning 3. by; Aaron Havens,; Abhishek Gupta, … 249 views ...

Overcoming Exploration in Reinforcement Learning with Demonstrations

ashvin.me

Overcoming Exploration in Reinforcement Learning with Demonstrations. Ashvin Nair, Bob McGrew, Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel.

Scites for Reinforcement Learning with Deep Energy-Based Policies

scirate.com

Toggle navigation SciRate beta. Sign in · Sign up. Reinforcement Learning with Deep Energy-Based Policies. https://scirate.com/arxiv Scites. Ashvin Nair. Daniel Suess. Noon van der Silk. Paul Mathews. Peter Wittek · About · Legal. Sponsored by Draftable.

[ v1] Overcoming Exploration in Reinforcement Learning with...

128.84.21.199

Authors: Ashvin Nair, Bob McGrew, Marcin Andrychowicz, Wojciech Zaremba, Pieter Abbeel. (Submitted on 28 Sep 2017). Abstract: Exploration in environments with sparse rewards has been a persistent problem in reinforcement learning (RL). Many tasks are natural to specify with a sparse reward, and ...

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