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从多个演示中学习控制

Learning for Control from Multiple Demonstrations
课程网址: http://videolectures.net/icml08_coates_lcmd/  
主讲教师: Adam Coates
开课单位: 百度公司
开课时间: 2008-08-12
课程语种: 英语
中文简介:
当给出来自次优专家的少量演示时,我们考虑学习遵循期望轨迹的问题。我们提出了一种算法,该算法(i)从次优化专家的演示中提取最初未知的期望轨迹,以及(ii)学习适合于沿着学习轨迹控制的局部模型。我们将算法应用于自主直升机飞行问题。在所有情况下,自主直升机的性能超过了我们的专家直升机飞行员的演示。更强大,我们的结果显着扩展了自主直升机特技飞行的最新技术水平。特别是,我们的成果包括第一次自主演奏,环路和飓风,在先前进行的特技飞行演习(例如现场翻转和翻滚)以及完整的航展上表现出极佳的性能,这需要在这些和其他各种演习之间进行自动过渡。
课程简介: We consider the problem of learning to follow a desired trajectory when given a small number of demonstrations from a sub-optimal expert. We present an algorithm that (i) extracts the---initially unknown---desired trajectory from the sub-optimal expert's demonstrations and (ii) learns a local model suitable for control along the learned trajectory. We apply our algorithm to the problem of autonomous helicopter flight. In all cases, the autonomous helicopter's performance exceeds that of our expert helicopter pilot's demonstrations. Even stronger, our results significantly extend the state-of-the-art in autonomous helicopter aerobatics. In particular, our results include the first autonomous tic-tocs, loops and hurricane, vastly superior performance on previously performed aerobatic maneuvers (such as in-place flips and rolls), and a complete airshow, which requires autonomous transitions between these and various other maneuvers.
关 键 词: 次优专家; 少量演示; 期望轨迹
课程来源: 视频讲座网
最后编审: 2019-04-18:cwx
阅读次数: 95