10.5281/zenodo.3936610
https://zenodo.org/records/3936610
oai:zenodo.org:3936610
Jonas Gonzalez-BIllandon
Jonas Gonzalez-BIllandon
Italian Institute of technology, University of Genova
Lukas Grasse
Lukas Grasse
University of Lethbridge
Alessandra Sciutti
Alessandra Sciutti
Italian Institute of technology
Matthew Tata
Matthew Tata
University of Lethbridge
Francesco Rea
Francesco Rea
Italian Institute of technology
Cognitive Architecture for Joint Attentional Learning of word-object mapping with a Humanoid Robot
Zenodo
2019
Self supervised learning
Deep Learning
Cognitive development
2019-11-08
10.5281/zenodo.3936609
Creative Commons Attribution 4.0 International
Since infancy humans can learn from social context to associate words with their meanings, for example associating names with objects. The open-question is which computational framework could replicate the abilities of toddlers in developing language and its meaning in robots. We propose a computational framework in this paper to be implemented on a robotics platform to replicate the early learning process of humans for the specific task of word-object mapping.