C2RL: Convolutional-Contrastive Learning for Reinforcement Learning Based on Self-Pretraining for Strong Augmentation.

Park, Sanghoon; Kim, Jihun; Jeong, Han-You; Kim, Tae-Kyoung; Yoo, Jinwoo

Park, Sanghoon; Kim, Jihun; Jeong, Han-You; Kim, Tae-Kyoung; Yoo, Jinwoo.

Afiliação

Park S; Graduate School of Automotive Engineering, Kookmin University, Seoul 02707, Republic of Korea.
Kim J; Graduate School of Automotive Engineering, Kookmin University, Seoul 02707, Republic of Korea.
Jeong HY; Department of Electrical Engineering, Pusan National University, Busan 46241, Republic of Korea.
Kim TK; Department of Electronic Engineering, Gachon University, Seongnam 13120, Republic of Korea.
Yoo J; Department of Automobile and IT Convergence, Kookmin University, Seoul 02707, Republic of Korea.

Sensors (Basel) ; 23(10)2023 May 21.

Article em En | MEDLINE | ID: mdl-37430860

Palavras-chave

contrastive learning; data augmentation; deep reinforcement learning; generalization; network randomization; self-supervised learning

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article