End-to-End Autonomous Exploration with Deep Reinforcement Learning and Intrinsic Motivation

Developing artificial intelligence (AI) agents is challenging for efficient exploration in visually rich and complex environments. In this study, we formulate the exploration question as a reinforcement learning problem and rely on intrinsic motivation to guide exploration behavior. Such intrinsic m...

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Detalles Bibliográficos
Autores principales: Ruan, Xiaogang, Li, Peng, Zhu, Xiaoqing, Yu, Hejie, Yu, Naigong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8702337/
https://www.ncbi.nlm.nih.gov/pubmed/34956359
http://dx.doi.org/10.1155/2021/9945044

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8702337/
https://www.ncbi.nlm.nih.gov/pubmed/34956359
http://dx.doi.org/10.1155/2021/9945044

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