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Design of Experiments for Reinforcement Learning. 2015 ed.
・ISBN 978-3-319-12196-3 hard EUR 99.99
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| 著者・編者 | Gatti, Christopher, |
|---|---|
| シリーズ | (Springer Theses) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2014 |
| ページ数 | 191 pp. |
| 言語 | ENG |
| ニュース番号 | <A05-47257> |
解説
This thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge. The author approaches these entities using design of experiments not commonly employed to study machine learning methods. The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems.