图 书 馆
自动发现和MAXQ层次转移Automatic Discovery and Transfer of MAXQ Hierarchies |
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| 课程网址: | http://videolectures.net/icml08_mehta_adt/ |
| 主讲教师: | Neville Mehta |
| 开课单位: | 俄勒冈州立大学 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful trajectory from a source reinforcement learning task. HI-MAT discovers subtasks by analyzing the causal and temporal relationships among the actions in the trajectory. Under appropriate assumptions, HI-MAT induces hierarchies that are consistent with the observed trajectory and have compact value-function tables employing safe state abstractions. We demonstrate empirically that HI-MAT constructs compact hierarchies that are comparable to manually-engineered hierarchies and facilitate significant speedup in learning when transferred to a target task. |
| 关 键 词: | 计算机科学; 强化学习; 贝叶斯网络模型 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-11-16：cwx |
| 阅读次数: | 38 |