Interactive Hierarchical Task Learning from a Single Demonstration
Interactive Hierarchical Task Learning from a Single Demonstration
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从单个演示中学习交互式分层任务
DOI：
10.1145/2696454.2696474
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Daniel Miller
中科院分区：
文献类型：
--
作者：
Anahita Mohseni;C. Rich;S. Chernova;C. Sidner;Daniel Miller
我们已经开发了学习和互动算法，以在与双向交流的混合互动的背景下使用单个演示来支持人类教学等级任务模型。特别是，我们已经确定并实施了两个重要的启发式方法，以根据操纵工件的物理结构以及任务之间的数据流来建议任务分组。我们已经在模拟环境中评估了与用户的算法，并表明总体方法是可用的，并且分组建议显着改善了学习和互动。类别和主题描述符I.2.9 [人工智能]：机器人技术
We have developed learning and interaction algorithms to support a human teaching hierarchical task models to a robot using a single demonstration in the context of a mixedinitiative interaction with bi-directional communication. In particular, we have identified and implemented two important heuristics for suggesting task groupings based on the physical structure of the manipulated artifact and on the data flow between tasks. We have evaluated our algorithms with users in a simulated environment and shown both that the overall approach is usable and that the grouping suggestions significantly improve the learning and interaction. Categories and Subject Descriptors I.2.9 [Artificial Intelligence]: Robotics