Learning Similar Tasks From Observation and Practice

Learning Similar Tasks From Observation and Practice
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从观察和实践中学习类似的任务

DOI:
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发表时间:
2006
期刊:
2006 IEEE/RSJ International Conference on Intelligent Robots and Systems
影响因子:
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通讯作者:
G. Cheng
G. Cheng
中科院分区:
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文献类型:
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作者:
D. Bentivegna;C. Atkeson;G. Cheng

文献摘要

被引文献

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本文介绍了一个案例研究学习选择行为基元,并从观察和实践中产生子目标。我们的方法使用局部特征来概括任务,使用全局特征来从实践中学习。我们证明这种方法适用于大理石迷宫任务。我们的机器人使用本地功能,最初学习原始的选择和子目标生成策略,从观察教师操纵大理石通过迷宫。然后机器人在试图穿越另一个迷宫时使用这些信息,并在从实践中学习的过程中完善这些信息
This paper presents a case study of learning to select behavioral primitives and generate subgoals from observation and practice. Our approach uses local features to generalize across tasks and global features to learn from practice. We demonstrate this approach applied to the marble maze task. Our robot uses local features to initially learn primitive selection and subgoal generation policies from observing a teacher maneuver a marble through a maze. The robot then uses this information as it tries to traverse another maze, and refines the information during learning from practice