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In this interactive demo, we introduce a novel approach to grounded concept learning. Using the language game methodology, we set up a tutor-learner scenario where the learner is an autonomous agent, grounded in the world using a Nao humanoid robot, and the participant is its tutor. For each concept, the robot has to find out which data streams are important and what the typical values for each data stream within a concept are. To make these decisions, the learner makes use of the notion of discrimination, i.e. separating one particular object from the other objects in the scene. Over the course of many such interactions, the learner incrementally and in real-time builds a complete repertoire of concepts that is functional in the world. A video of the demonstration can be found at https://ehai.ai. vub.ac.be/demos/interactive-concept-learning.
Original languageEnglish
Title of host publicationProceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019)
EditorsKatrien Beuls, Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe, Paul Van Eecke
PublisherCEUR Workshop Proceedings
Number of pages2
Volume2491
ISBN (Electronic)1613-0073
Publication statusPublished - 8 Nov 2019
EventBNAIC 2019 - Brussels, Belgium
Duration: 7 Nov 20198 Nov 2019

Conference

ConferenceBNAIC 2019
CountryBelgium
CityBrussels
Period7/11/198/11/19

ID: 48202459