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Titlebook: Robot Learning from Human Teachers; Sonia Chernova,Andrea L. Thomaz Book 2014 Springer Nature Switzerland AG 2014

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發(fā)表于 2025-3-21 18:46:23 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Robot Learning from Human Teachers
編輯Sonia Chernova,Andrea L. Thomaz
視頻videohttp://file.papertrans.cn/832/831053/831053.mp4
叢書名稱Synthesis Lectures on Artificial Intelligence and Machine Learning
圖書封面Titlebook: Robot Learning from Human Teachers;  Sonia Chernova,Andrea L. Thomaz Book 2014 Springer Nature Switzerland AG 2014
描述Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstra
出版日期Book 2014
版次1
doihttps://doi.org/10.1007/978-3-031-01570-0
isbn_softcover978-3-031-00442-1
isbn_ebook978-3-031-01570-0Series ISSN 1939-4608 Series E-ISSN 1939-4616
issn_series 1939-4608
copyrightSpringer Nature Switzerland AG 2014
The information of publication is updating

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發(fā)表于 2025-3-21 23:08:58 | 只看該作者
Book 2014social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstra
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Robot Learning from Human Teachers978-3-031-01570-0Series ISSN 1939-4608 Series E-ISSN 1939-4616
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發(fā)表于 2025-3-23 01:06:50 | 只看該作者
Refining a Learned Task,rner’s exploration. In general, this is a complex process where the teacher dynamically adjusts their support based on the learners demonstrated skill level. The learner, in turn, helps the instructor by making their learning process transparent through communicative acts, and by demonstrating their current knowledge and mastery of the task.
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Book 2014 into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts
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1939-4608 has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not roboti
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