| 书目名称 | Design of Experiments for Reinforcement Learning |
| 编辑 | Christopher Gatti |
| 视频video | http://file.papertrans.cn/269/268711/268711.mp4 |
| 概述 | Nominated by the Rensselaer Polytechnic Institute as an outstanding Ph.D. thesis.Explains reinforcement learning through a range of problems by exploring what affects reinforcement learning and what c |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | 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.. |
| 出版日期 | Book 2015 |
| 关键词 | Kriging Covariance Functions; Reinforcement Learning Algorithm; Response Surface Metamodeling; Sequent |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-12197-0 |
| isbn_softcover | 978-3-319-38551-8 |
| isbn_ebook | 978-3-319-12197-0Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer International Publishing Switzerland 2015 |