Social Learning for Intelligent Characters (SLICE)

Type: National Project

Duration: from 2018 Oct 01 to 2021 Sep 30

Financed by: FCT

Prime Contractor: INESC-ID (Other)

This project's objective is to develop and validate an authoring-friendly framework for the creation of transparent social intelligent agents capable of being deployed as virtual characters in training simulations or games, or used to drive the behavior of social robots. This framework joins two until now disparate areas of artificial intelligence research, namely, social agent architectures and machine learning. By using machine learning techniques over a solid social theory foundation that defines the structure of the learning task, our framework provides a new methodology where authors can create intelligent characters by providing examples of social interaction. Since the learned behaviour will be built on top of a social representation model, it will be more understandable and transparent to the authors, thus allowing a finer level of control. We will validate our approach in two ways, one with authors, and another with end-users via a case study in interview training

Partnerships

  • INESC-ID (Other)

Principal Investigators

Members