Published November 28, 2019 | Version v1
Conference paper Open

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

  • 1. Istituto Italiano di Tecnologia
  • 2. University of Hertfordshire Hatfield, Dept. of Computer Science

Description

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.

Files

CopyrightReceipt.pdf

Files (1.1 MB)

Name Size Download all
md5:47de8cae8371916c41caa21ec30a1ab9
19.5 kB Preview Download
md5:fca268d06def51537f7fdf7017db173e
1.1 MB Preview Download

Additional details

Funding

wHiSPER – investigating Human Shared PErception with Robots 804388
European Commission