Papers › Modern Deep Reinforcement Learning Algorithms

Modern Deep Reinforcement Learning Algorithms

24 Jun 2019arXiv:1906.10025archive 2025-07-28

Sergey Ivanov, Alexander D'yakonov

Recent advances in Reinforcement Learning, grounded on combining classical theoretical results with Deep Learning paradigm, led to breakthroughs in many artificial intelligence tasks and gave birth to Deep Reinforcement Learning (DRL) as a field of research. In this work latest DRL algorithms are reviewed with a focus on their theoretical justification, practical limitations and observed empirical properties.

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FortsAndMills/Learning-Reinforcement-Learning officialmentioned in papermentioned on GitHubpytorch report

TristanBertin/Reinforcement_Learning mentioned on GitHubtf report

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Deep Reinforcement Learning Reinforcement Learning Reinforcement Learning (RL)reinforcement-learning

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