Titlebook: Deep Reinforcement Learning; Fundamentals, Resear Hao Dong,Zihan Ding,Shanghang Zhang Book 2020 Springer Nature Singapore Pte Ltd. 2020 Dee

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书目名称Deep Reinforcement Learning影响因子(影响力)




书目名称Deep Reinforcement Learning影响因子(影响力)学科排名




书目名称Deep Reinforcement Learning网络公开度




书目名称Deep Reinforcement Learning网络公开度学科排名




书目名称Deep Reinforcement Learning被引频次




书目名称Deep Reinforcement Learning被引频次学科排名




书目名称Deep Reinforcement Learning年度引用




书目名称Deep Reinforcement Learning年度引用学科排名




书目名称Deep Reinforcement Learning读者反馈




书目名称Deep Reinforcement Learning读者反馈学科排名

palliative-care

OPINE

Parallel

brother

Cloudburst

Combine Deep ,-Networks with Actor-Criticral networks to approximate the optimal action-value functions. It receives only the pixels as inputs and achieves human-level performance on Atari games. Actor-critic methods transform the Monte Carlo update of the REINFORCE algorithm into the temporal-difference update for learning the policy para

Cloudburst

Challenges of Reinforcement Learning; (2) stability of training; (3) the catastrophic interference problem; (4) the exploration problems; (5) meta-learning and representation learning for the generality of reinforcement learning methods across tasks; (6) multi-agent reinforcement learning with other agents as part of the environment;

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Imitation Learningtential approaches, which leverages the expert demonstrations in sequential decision-making process. In order to provide the readers a comprehensive understanding about how to effectively extract information from the demonstration data, we introduce the most important categories in imitation learnin

Interstellar

Endearing