Book
Deep Reinforcement Learning Fundamentals, Research and Applications
| Identifier | --haodongzih-472 |
|---|---|
| Penulis / Pengarang | Hao Dong, Zihan Ding, Shanghang Zhang |
| Kata Kunci | Deep Learning Research Applications |
| Tanggal Publikasi | 18 Apr 2020 |
| Bahasa | Bahasa Inggris |
| Abstrak / Deskripsi | Deep reinforcement learning (DRL) combines deep learning (DL) with a reinforcement learning (RL) architecture. It has been able to perform a wide range of complex decision-making tasks that were previously intractable for a machine. Moreover, DRL has contributed to the recent great successes in artiï¬Âcial intelligence (AI) like AlphaGo and OpenAI Five. Indeed, DRL has opened up many exciting avenues to explore in a variety of domains such as healthcare, robotics, smart grids, and ï¬Ânance. |
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2020 Deep Reinforcement Learning Fundamentals, Research and Applications by Hao Dong (editor), Zihan Ding (editor)a.pdf
Deep reinforcement learning (DRL) combines deep learning (DL) with a reinforcement learning (RL) architecture.…
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application/pdf | 11,4 MB | ⬇️ Buka / Download |
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