图 书 馆
稀疏核Sarsa（λ）一个合格的痕迹Sparse Kernel-SARSA(λ) with an Eligibility Trace |
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| 课程网址: | http://videolectures.net/ecmlpkdd2011_robards_eligibility/ |
| 主讲教师: | Matthew Robards |
| 开课单位: | 澳大利亚国立大学 |
| 开课时间: | 2011-11-30 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We introduce the first online kernelized version of SARSA(λ) to permit sparsification for arbitrary λ for 0 ≤ λ ≤ 1; this is possible via a novel kernelization of the eligibility trace that is maintained separately from the kernelized value function. This separation is crucial for preserving the functional structure of the eligibility trace when using sparse kernel projection techniques that are essential for memory efficiency and capacity control. The result is a simple and practical Kernel-SARSA(λ) algorithm for general 0 ≤ λ ≤ 1 that is memory-efficient in comparison to standard SARSA(λ) (using various basis functions) on a range of domains including a real robotics task running on a Willow Garage PR2 robot. |
| 关 键 词: | 稀疏核投影技术; 存储效率; 容量控制; 机器人 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-06：魏雪琼(课程编辑志愿者) |
| 阅读次数: | 486 |