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Multi-Agent Machine Learning: A Reinforcement Approach H. M. Schwartz 第1 版本
Multi-Agent Machine Learning: A Reinforcement Approach
H. M. Schwartz
The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces.
256 pages
| 介质类型 | 图书 Hardcover Book (精装硬皮书) |
| 已发行 | 2014年9月26日 |
| ISBN13 | 9781118362082 |
| 出版商 | John Wiley & Sons Inc |
| 页数 | 256 |
| 商品尺寸 | 238 × 163 × 18 mm · 478 g |
| 语言 | 英语 |
