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非参数化策略梯度：命题和关系域的统一处理Non-Parametric Policy Gradients: A Unified Treatment of Propositional and Relational Domains |
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| 课程网址: | http://videolectures.net/icml08_driessens_npp/ |
| 主讲教师: | Kurt Driessens |
| 开课单位: | 鲁汶大学 |
| 开课时间: | 2008-08-04 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Policy gradient approaches are a powerful instrument for learning how to interact with the environment.Existing approaches have focused on propositional and continuous domains only. Without extensive feature engineering, it is difficult -- if not impossible -- to apply them within structured domains, in which e.g. there is a varying number of objects and relations among them. In this paper, we describe a non-parametric policy gradient approach -- called NPPG -- that overcomes this limitation. The key idea is to apply Friedmann's gradient boosting: policies are represented as a weighted sum of regression models grown in an stage-wise optimization. Employing off-the-shelf regression learners, NPPG can deal with propositional, continuous, and relational domains in a unified way. Our experimental results show that it can even improve on established results. |
| 关 键 词: | 政策梯度法; 策略梯度方法; 功能梯度 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-03：张荧(课程编辑志愿者) |
| 阅读次数: | 155 |