Studying How Innate Motivations Can Drive Skill Acquisition in Cognitive Robots
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Universidade da Coruña
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- Alberto Alvarellos González (ed. lit.)
- José Joaquim de Moura Ramos (ed. lit.)
- Beatriz Botana Barreiro (ed. lit.)
- Javier Pereira Loureiro (ed. lit.)
- Manuel F. González Penedo (ed. lit.)
Publisher: MDPI
ISBN: 978-3-03921-444-0, 978-3-03921-443-3
Year of publication: 2019
Congress: XoveTIC (2. 2019. A Coruña)
Type: Conference paper
Abstract
In this paper, we address the problem of how to bootstrap a cognitive architecture to opportunistically start learning skills in domains where multiple skills can be learned at the same time. To this end, taking inspiration from a series of computational models of the use of motivations in infants, we propose an approach that leverages two types of cognitive motivations: exploratory and proficiency based, the latter modulated by the concept of interestingness as an implementation of attentional mechanisms. This approach is tested in an illustrative experiment with a real robot.