Advancing intuitive human-machine interaction with human-like social capabilities for education in schools




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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 765955

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ESR14 - Socio-affective effects on the degree of human-robot cooperation


Silvia Tulli is a PhD student at  INESC-ID supervised by Ana Paiva, in association with Catherine Pelachaud and Pierre Dillenbourg. She obtained her Master Degree in Human-Computer Interaction at the University of Trento, an interdisciplinary program offered by the departments of Information Engineering and Computer Science, Psychology and Cognitive Science. She did a research period into the Human Interfaces in Information Systems Laboratory (HIIS, at CNR of Pisa) during while she works on adaptive serious games for mild cognitive impairment, end-user development for IoT system and social robots. She would like to delve deeper into co-adaptive human-robot interactive systems and the definition of the primitives for the implementation of efficient socio-affective HRI. 

Main host institution: INESC-ID

Supervisor: Ana Paiva (INESC-ID), in association with Catherine Pelachaud (UPMC) and Pierre Dillenbourg (EPFL)

Secondment institution: UPMC; EPFL

Objectives: There is huge potential in using social robots to help children learn more effectively in a large variety of domains. One important issue to consider is the social role that the robot should enact. Namely, it can act as a teacher that explains and presents didactic content to the children that it interacts with. Alternatively, the robot can act more as a peer or a companion that practices alongside others. It can also act as a student that children would have to teach and correct its mistakes. All these different roles have important design implications for how the robot should behave and also how the learning experience is structured. These need to be addressed properly to promote a cooperative stance between the robot and the human learner. Cultural factors will also determine the expectations regarding each different pedagogical role. This ESR project will analyse such implications and will focus on the social aspects associated to these different roles. The aim is to develop a computational model of general decision-making that allows a robot to model others from a relational perspective and adapt its expectations of cooperative behaviour accordingly. More specifically, the proposed model will enable the robot to have a better understanding of how it is perceived by learners and how appropriate are its requests during the learning tasks. 


Expected results: Completed draft of PhD dissertation; implementation of computational model for robots designed to teach children, several publications in international journals and peer-reviewed conferences 


For further information, contact:  Ana Paiva

ANIMATAS – MSCA – ITN – 2017 - 765955 2