Adaptive Estimation of Emotion Generation for an Ambient Agent Model

摘要

To improve the performance and wellbeing of humans in complex human-computer interaction settings, an interesting challenge for an ambient (or pervasive) agent system is to recognise the emotions of humans. To this end, this paper introduces a computational model to estimate the process of emotion generation based on certain triggers. The model has been implemented and tested using the modelling language LEADSTO. A first evaluation indicates that the model is successful in estimating a person's emotions, and is robust to different parameter settings.