图 书 馆
未知因素动态下基于非策略模型的学习Off-policy Model-based Learning under Unknown Factored Dynamics |
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| 课程网址: | http://videolectures.net/icml2015_hallak_unknown_factored_dynamic... |
| 主讲教师: | Assaf Hallak |
| 开课单位: | 以色列理工学院 |
| 开课时间: | 2015-09-27 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Off-policy learning in dynamic decision problems is essential for providing strong evidence that a new policy is better than the one in use. But how can we prove superiority without testing the new policy? To answer this question, we introduce the G-SCOPE algorithm that evaluates a new policy based on data generated by the existing policy. Our algorithm is both computationally and sample efficient because it greedily learns to exploit factored structure in the dynamics of the environment. We present a finite sample analysis of our approach and show through experiments that the algorithm scales well on high-dimensional problems with few samples. |
| 关 键 词: | 动态决策; 数据评估; 高维问题 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2022-11-06：chenjy |
| 最后编审: | 2022-11-06：chenjy |
| 阅读次数: | 37 |