{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T18:37:45Z","timestamp":1775155065543,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2016,2,22]],"date-time":"2016-02-22T00:00:00Z","timestamp":1456099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/robotics5010006","type":"journal-article","created":{"date-parts":[[2016,2,22]],"date-time":"2016-02-22T10:24:17Z","timestamp":1456136657000},"page":"6","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Application of the Naive Bayes Classifier for Representation and Use of Heterogeneous and Incomplete Knowledge in Social Robotics"],"prefix":"10.3390","volume":"5","author":[{"given":"Gabriele","family":"Trovato","sequence":"first","affiliation":[{"name":"Graduate School of Advanced Science and Engineering, Waseda University, Tokyo 162-0044, Japan"}]},{"given":"Grzegorz","family":"Chrupa\u0142a","sequence":"additional","affiliation":[{"name":"Department of Communication and Information Sciences, Tilburg School of Humanities, Tilburg University, Tilburg PO Box 90153, 5000 LE, The Netherlands"}]},{"given":"Atsuo","family":"Takanishi","sequence":"additional","affiliation":[{"name":"Department of Modern Mechanical Engineering, Waseda University; Humanoid Robotics Institute (HRI), Waseda University, Tokyo 162-8480, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2016,2,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1162\/neco.1996.8.7.1341","article-title":"The Lack of a Priori Distinctions between Learning Algorithms","volume":"8","author":"Wolpert","year":"1996","journal-title":"Neural Comput."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s10339-011-0404-1","article-title":"Model learning for robot control: A survey","volume":"12","author":"Peters","year":"2011","journal-title":"Cogn. 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