Eager to Learn vs. Quick to Complain? How a socially adaptive robot architecture performs with different robot personalities

TitleEager to Learn vs. Quick to Complain? How a socially adaptive robot architecture performs with different robot personalities
Publication TypeConference Paper
Year of Publication2019
AuthorsTanevska, A, Rea, F, Sandini, G, Cañamero, L, Sciutti, A
Name of ProceedingsProc. 2019 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2019)
Pagination365–371
Date Published10/2019
PublisherIEEE
Conference LocationBari, Italy
Abstract

A social robot that is aware of our needs and continuously adapts its behaviour to them has the potential of creating a complex, personalized, human-like interaction of the kind we are used to have with our peers in our everyday lives. We are interested in exploring how would an adaptive architecture function and personalize to different users when given different initial values of its variables, i.e. when implementing the same adaptive framework with different robot personalities. Would an architecture that learns very quickly outperform a slower but steadier learning profile? To further explore this, we propose a cognitive architecture for the humanoid robot iCub supporting adaptability and we attempt to validate its functionality and test different robot profiles.

URLhttps://ieeexplore.ieee.org/document/8913903
DOI10.1109/SMC.2019.8913903