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A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning - Foundations and Trends (R) in Machine Learning Alborz Geramifard
A Tutorial on Linear Function Approximators for Dynamic Programming and Reinforcement Learning - Foundations and Trends (R) in Machine Learning
Alborz Geramifard
A Markov Decision Process (MDP) is a natural framework for formulating sequential decision-making problems under uncertainty. In recent years, researchers have greatly advanced algorithms for learning and acting in MDPs. This book reviews such algorithms.
92 pages
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2013年12月19日 |
| ISBN13 | 9781601987600 |
| 出版社 | now publishers Inc |
| ページ数 | 92 |
| 寸法 | 156 × 234 × 5 mm · 140 g |
| 言語 | 英語 |
