Tutorial: Player Modelling through Affective Computing

Phil Lopes (Universidade Lus�fona de Humanidades e Tecnologias, Lisboa) and David Melhart (University of Malta, Malta), Abstract: Affective computing is a field of computer science that focuses on the sensing and prediction of affect and emotions. Games provide a rich and robust testbed for affective computing applications due to a unique mix of constrained environment and emergent interaction. However, affective computing also has value to game research for both academic and industrial applications. Methodologies lifted from affective computing can help game researchers build more robust predictive models of not just behaviour but also player experience.
This tutorial aims to introduce affective computing concepts and methods for player modelling. The first part of the tutorial gives a broad overview of the field of affective computing in the games domain including fundamental concepts, best practices, tools, and industry applications. The second part of the tutorial focuses on the frontiers of affective computing research in games and touch on the topics of VR and research into embodied cognition.