Abstract : Children seem intrinsically motivated to manipulate, to ex- plore, to test, to learn and they look for activities and situations that provide such learning opportunities. Inspired by research in developmental psychology and neuroscience, some researchers have started to address the problem of designing intrinsic motivation systems. A robot controlled by such systems is able to autonomously explore its environment not to fulfil predefined tasks but driven by an incentive to search for situations where learning happens efficiently. In this paper, we present the ori- gins of these intrinsically motivated machines, our own research in this novel field and we argue that intrinsic motivation might be a crucial step towards machines capable of life-long learning and open-ended development.
Type de document :
Chapitre d'ouvrage
Lungarella, M.; Iida, F.; Bongard, J.; Pfeifer, R. 50 Years of AI, Lungarella, M.; Iida, F.; Bongard, J.; Pfeifer, R., pp.n/a, 2008
https://hal.inria.fr/inria-00420223
Contributeur : Jérôme Béchu
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Soumis le : lundi 28 septembre 2009 - 14:23:05
Dernière modification le : jeudi 16 novembre 2017 - 17:12:01
Document(s) archivé(s) le : mercredi 16 juin 2010 - 00:10:14
Frederic Kaplan, Pierre-Yves Oudeyer. Intrinsically motivated machines. Lungarella, M.; Iida, F.; Bongard, J.; Pfeifer, R. 50 Years of AI, Lungarella, M.; Iida, F.; Bongard, J.; Pfeifer, R., pp.n/a, 2008. 〈inria-00420223〉
