Deep Reinforcement Learning: Fundamentals, Research and Applications von Dong, Hao, Ding, Zihan, Zhang, Shanghang

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Cohort Profile: South China Cohort von Yang, Jialu, Luo, Shiyun, Liu, Yan, Hong, Minghuang, Qiu, Xiaoqiang, Lin, Yingzi, Zhang, Weisen, Gao, Peisong, Li, Zhibin, Hu, Zhijian, Xia, Min

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Hydrocephalus induced via intraventricular kaolin injection in adult rats von Shaolin, Zhang, Zhanxiang, Wang, Hao, Xu, Feifei, Zhang, Caiquan, Huang, Donghan, Chen, Jianfeng, Bao, Feng, Liu, Shanghang, Shen

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Introduction to Reinforcement Learning von Ding, Zihan, Huang, Yanhua, Yuan, Hang, Dong, Hao

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Taxonomy of Reinforcement Learning Algorithms von Zhang, Hongming, Yu, Tianyang

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Deep Q-Networks von Huang, Yanhua

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Challenges of Reinforcement Learning von Ding, Zihan, Dong, Hao

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AlphaZero von Zhang, Hongming, Yu, Tianyang

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Multi-Agent Reinforcement Learning von Zhang, Huaqing, Zhang, Shanghang

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EfficientBioAI: Making Bioimaging AI Models Efficient in Energy and Latency von Zhou, Yu

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Hierarchical Reinforcement Learning von Huang, Yanhua

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Introduction to Deep Learning von Zhang, Jingqing, Yuan, Hang, Dong, Hao

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Imitation Learning von Ding, Zihan

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Combine Deep Q-Networks with Actor-Critic von Zhang, Hongming, Yu, Tianyang, Huang, Ruitong

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Effect of Current Densities on the Electrochemical Behavior of a Flat Plate Pb-Ag Anode for Zinc Electrowinning von Liang-Xing, JIANG, Shui-Ping, ZHONG, Yan-Qing, LAI, LüXiao-Jun, Bo, HONG, Hong-Jian, PENG, Xiang-Yang, ZHOU, Jie, LI, Ye-Xiang, LIU

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Learning to Run von Ding, Zihan, Dong, Hao

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Robot Learning in Simulation von Ding, Zihan, Dong, Hao

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Algorithm Table von Ding, Zihan

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Integrating Learning and Planning von Zhang, Huaqing, Huang, Ruitong, Zhang, Shanghang

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Policy Gradient von Huang, Ruitong, Yu, Tianyang, Ding, Zihan, Zhang, Shanghang

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