Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research

JJ Garau-Luis, E Crawley, B Cameron - arXiv preprint arXiv:2107.03015, 2021 - arxiv.org
Deep Reinforcement Learning (DRL) is considered a potential framework to improve many
real-world autonomous systems; it has attracted the attention of multiple and diverse fields …
被引用次数：5 相关文章

Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research

JJ Garau-Luis, E Crawley, B Cameron - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Abstract Deep Reinforcement Learning (DRL) is considered a potential framework to
improve many real-world autonomous systems; it has attracted the attention of multiple and …
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[PDF][PDF] Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research

JJ Garau-Luis, E Crawley, B Cameron - 2021 - systemarchitect.mit.edu
Abstract Deep Reinforcement Learning (DRL) is considered a potential framework to
improve many realworld autonomous systems; it has attracted the attention of multiple and …