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Multi-Agent Machine Learning: A Reinforcement Approach H. M. Schwartz 1. izdevums
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
| Mediji | Grāmatas Hardcover Book (Grāmata ar cieto muguriņu un vāku) |
| Izlaists | 2014. gada 26. septembris |
| ISBN13 | 9781118362082 |
| Izdevēji | John Wiley & Sons Inc |
| Lapas | 256 |
| Izmēri | 238 × 163 × 18 mm · 478 g |
| Valoda | Angļu |