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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書目名稱Deep Reinforcement Learning影響因子(影響力)




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書目名稱Deep Reinforcement Learning網(wǎng)絡公開度




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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