Emoticontrol: Emotions-based Control of User-Interfaces Adaptations

Abstract

Emotions are integral to human nature, and their existence, duration, and evolution could lead to specific behaviors. If emotions and behaviors are ignored in the design of socio-technical systems, they will fail or cause discomfort. User interfaces (UIs) are elements of interactive systems able to trigger or moderate emotions. UIs are increasingly designed adaptive to users' various characteristics, intending to improve their satisfaction, performance, and decisions. However, previous adaptation supervising approaches are not effectively adopted in real life since they neglect the dynamic behaviors of humans or systems. This paper proposes Emoticontrol, a quality-driven approach to adapting UIs to users' emotions using Model-Free Reinforcement Learning (MFRL). The approach aims to maximize applying the essential adaptations and minimize the unnecessary ones towards users' enhanced quality of experience (QoE). The approach also considers improving the software quality of service (QoS) by designing software architecture alternatives. We chose emergency evacuation training as a suitable evaluation domain since people experience intense emotions in potential danger. We performed experiments with a mobile application we developed that acts as a recommender system in evacuation training. By taking contextual input of the users' basic emotions from face recognition, the application intelligently adapts its UI to quickly lead people to safe areas while keeping them emotionally controlled. We consider software performance a crucial QoS; thus, we adopt and test architectures that facilitate an acceptable level of performance. The evaluation process confirms the efficiency and effectiveness of the MFRL in iterations, as well as compared to other UI adaptation techniques.