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CURL: Contrastive Unsupervised Representations for Reinforcement Learning

2020-04-08 17:40:43
Aravind Srinivas, Michael Laskin, Pieter Abbeel
arXiv_CV
         
Abstract

We present CURL: Contrastive Unsupervised Representations for Reinforcement Learning. CURL extracts high-level features from raw pixels using contrastive learning and performs off-policy control on top of the extracted features. CURL outperforms prior pixel-based methods, both model-based and model-free, on complex tasks in the DeepMind Control Suite and Atari Games showing 2.8x and 1.6x performance gains respectively at the 100K interaction steps benchmark. On the DeepMind Control Suite, CURL is the first image-based algorithm to nearly match the sample-efficiency and performance of methods that use state-based features.

Abstract (translated)

URL

https://arxiv.org/abs/2004.04136

PDF

https://arxiv.org/pdf/2004.04136.pdf

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