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Volume 5
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10.3390/robotics5010006
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Article

Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics

by
Gabriele Trovato
1,*,
Grzegorz Chrupała
2 and
Atsuo Takanishi
3
1
Graduate School of Advanced Science and Engineering, Waseda University, Tokyo 162-0044, Japan
2
Department of Communication and Information Sciences, Tilburg School of Humanities, Tilburg University, Tilburg PO Box 90153, 5000 LE, The Netherlands
3
Department of Modern Mechanical Engineering, Waseda University; Humanoid Robotics Institute (HRI), Waseda University, Tokyo 162-8480, Japan
*
Author to whom correspondence should be addressed.
Robotics 2016, 5(1), 6; https://doi.org/10.3390/robotics5010006
Submission received: 27 September 2015 / Revised: 18 January 2016 / Accepted: 14 February 2016 / Published: 22 February 2016
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Abstract

As societies move towards integration of robots, it is important to study how robots can use their cognition in order to choose effectively their actions in a human environment, and possibly adapt to new contexts. When modelling these contextual data, it is common in social robotics to work with data extracted from human sciences such as sociology, anatomy, or anthropology. These heterogeneous data need to be efficiently used in order to make the robot adapt quickly its actions. In this paper we describe a methodology for the use of heterogeneous and incomplete knowledge, through an algorithm based on naive Bayes classifier. The model was successfully applied to two different experiments of human-robot interaction.
Keywords: social robotics; statistical learning; human-robot interaction; adaptive robotics; incomplete knowledge social robotics; statistical learning; human-robot interaction; adaptive robotics; incomplete knowledge

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MDPI and ACS Style

Trovato, G.; Chrupała, G.; Takanishi, A. Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics. Robotics 2016, 5, 6. https://doi.org/10.3390/robotics5010006

AMA Style

Trovato G, Chrupała G, Takanishi A. Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics. Robotics. 2016; 5(1):6. https://doi.org/10.3390/robotics5010006

Chicago/Turabian Style

Trovato, Gabriele, Grzegorz Chrupała, and Atsuo Takanishi. 2016. "Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics" Robotics 5, no. 1: 6. https://doi.org/10.3390/robotics5010006

APA Style

Trovato, G., Chrupała, G., & Takanishi, A. (2016). Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics. Robotics, 5(1), 6. https://doi.org/10.3390/robotics5010006

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