The ITALK project : A developmental robotics approach to the study of individual, social, and linguistic learning

This is the peer reviewed version of the following article: Frank Broz et al, “The ITALK Project: A Developmental Robotics Approach to the Study of Individual, Social, and Linguistic Learning”, Topics in Cognitive Science, Vol 6(3): 534-544, June 2014, which has been published in final form at doi: http://dx.doi.org/10.1111/tops.12099 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving." Copyright © 2014 Cognitive Science Society, Inc.This article presents results from a multidisciplinary research project on the integration and transfer of language knowledge into robots as an empirical paradigm for the study of language development in both humans and humanoid robots. Within the framework of human linguistic and cognitive development, we focus on how three central types of learning interact and co-develop: individual learning about one's own embodiment and the environment, social learning (learning from others), and learning of linguistic capability. Our primary concern is how these capabilities can scaffold each other's development in a continuous feedback cycle as their interactions yield increasingly sophisticated competencies in the agent's capacity to interact with others and manipulate its world. Experimental results are summarized in relation to milestones in human linguistic and cognitive development and show that the mutual scaffolding of social learning, individual learning, and linguistic capabilities creates the context, conditions, and requisites for learning in each domain. Challenges and insights identified as a result of this research program are discussed with regard to possible and actual contributions to cognitive science and language ontogeny. In conclusion, directions for future work are suggested that continue to develop this approach toward an integrated framework for understanding these mutually scaffolding processes as a basis for language development in humans and robots.Peer reviewe

Contingency scaffolds language learning

In human robot interaction the question how to communicate is an important one. The answer to this question can be approached through several perspectives. One approach to study the best way how a robot should behave in an interaction with a human is by providing a consistent robotic behavior. From this we can gain insights into what parameters are triggering what responsive behavior in an user. This method allows us as roboticists to investigate how we can elicit a specific behavior in users in order to facilitate robot's learning. In previous studies, we have shown how responsive eye gaze and feedback on a looming detection is modifying the human tutoring behavior [1]. In this paper, we present a study was carried out within the ITALK project. The study is targeting, how we can tune robotic feedback strategies of the iCub robot to evoke a tutoring behavior in a human tutor that is supporting a language acquisition system. We used a longitudinal approach for the study to also verify the verbal feedback given by the robot