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强化学习的线性模型，线性值 - 函数逼近和特征选择分析An Analysis of Linear Models, Linear Value-Function Approximation, and Feature Selection for Reinforcement Learning |
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| 课程网址: | http://videolectures.net/icml08_parr_alm/ |
| 主讲教师: | Ronald Parr |
| 开课单位: | 杜克大学 |
| 开课时间: | 2008-08-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We show that linear value function approximation is equivalent to a form of linear model approximation. We derive a relationship between the model approximation error and the Bellman error, and show how this relationship can guide feature selection for model improvement and/or value function improvement. We also show how these results give insight into the behavior of existing feature-selection algorithms. |
| 关 键 词: | 线性值函数; 逼近误差; 特征选择算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-19：lxf |
| 阅读次数: | 102 |