Abstract

Abstract: In this short talk we will discuss research aimed at the integration of emotion interpretation methods with personalized decision support systems. Following non-cognitive models of emotions, our detection methods use physiological readings from wearable and mobile devices. Furthermore, we also use affective face expression analysis. We assume the use of the context-aware systems paradigm, where user affect is just one of the many dimensions of context. We analyze the affective data using the AWARE platform. For personalized decision support, we propose an understandable and explainable rule-based reasoning layer. In the talk we discuss selected tools we developed, as well as our recent experiments in affective computing oriented on personalization. In these experiments we use computer games as a controlled environment for affective stimulation.

Grzegorz J. Nalepa (http://GJN.re) is an engineer with degrees in computer science – artificial intelligence, and philosophy. He formulated the eXtended Tabular Trees rule representation method, as well as the Semantic Knowledge Engineering approach. He authored a book “Modeling with Rules using Semantic Knowledge Engineering” (Springer 2018). He co-edited a book “Synergies Between Knowledge Engineering and Software Engineering” (Springer 2018). He co-authored over 150 research papers in international conferences and journals. He coordinates GEIST - Group for Engineering of Intelligent Systems and Technologies (http://GEIST.re), and cooperates with AGH University and Jagiellonian University in Krakow, Poland. He is a member of Polish Artificial Intelligence Society (PSSI), IEEE , Italian Artificial Intelligence Society (AI*IA) and KES . His recent interests include context-aware systems, affective computing and explainable AI. He organised two editions of the AfCAI workhop on affective computing in Murcia (2016) and Valencia (2018), and the first edition of the XAILA workshop on explainable AI and law on the JURIX conference in Groningen (2018).