| 书目名称 | Data Mining for Social Robotics |
| 副标题 | Toward Autonomously |
| 编辑 | Yasser Mohammad,Toyoaki Nishida |
| 视频video | |
| 概述 | Reviews the key recent research in social robotics, learning from demonstration and imitation.Offers a detailed explanation of key algorithms in change discovery, motif discovery and causality analysi |
| 丛书名称 | Advanced Information and Knowledge Processing |
| 图书封面 |  |
| 描述 | .This book explores an approach to social robotics based solely on autonomous unsupervised techniques and positions it within a structured exposition of related research in psychology, neuroscience, HRI, and data mining. The authors present an autonomous and developmental approach that allows the robot to learn interactive behavior by imitating humans using algorithms from time-series analysis and machine learning. ..The first part provides a comprehensive and structured introduction to time-series analysis, change point discovery, motif discovery and causality analysis focusing on possible applicability to HRI problems. Detailed explanations of all the algorithms involved are provided with open-source implementations in MATLAB enabling the reader to experiment with them. Imitation and simulation are the key technologies used to attain social behavior autonomously in the proposed approach. Part two gives the reader a wide overview of research in these areas in psychology, and ethology. Based on this background, the authors discuss approaches to endow robots with the ability to autonomously learn how to be social. ..Data Mining for Social Robots. will be essential reading for gra |
| 出版日期 | Book 2015 |
| 关键词 | Change Point Discovery; Constrained Motif Discovery; Human Robot Interaction; Imitation Learning; Social |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-25232-2 |
| isbn_softcover | 978-3-319-79755-7 |
| isbn_ebook | 978-3-319-25232-2Series ISSN 1610-3947 Series E-ISSN 2197-8441 |
| issn_series | 1610-3947 |
| copyright | Springer International Publishing Switzerland 2015 |
发表于 2025-3-21 19:07:37
