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自适应k-气象学问题及其在强化学习中结构学习与特征选择中的应用The Adaptive k-Meteorologists Problem and Its Application to Structure Learning and Feature Selection in Reinforcement Learning |
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| 课程网址: | http://videolectures.net/icml09_diuk_akmp/ |
| 主讲教师: | Carlos Diuk |
| 开课单位: | 新泽西州立大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The purpose of this paper is three-fold. First, we formalize and study a problem of learning probabilistic concepts in the recently proposed KWIK framework. We give details of an algorithm, known as the Adaptive k-Meteorologists Algorithm, analyze its sample complexity upper bound, and give a matching lower bound. Second, this algorithm is used to create a new reinforcement learning algorithm for factoredstate problems that enjoys significant improvement over the previous state-of-the-art algorithm. Finally, we apply the Adaptive k-Meteorologists Algorithm to remove a limiting assumption in an existing reinforcement-learning algorithm. The effectiveness of our approaches are demonstrated empirically in a couple benchmark domains as well as a robotics navigation problem. |
| 关 键 词: | 概率概念; 自适应k气象学家算法; 强化学习算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-21：lxf |
| 阅读次数: | 70 |