Guidelines for Designing Computational Models of Emotions

Abstract

Rapid growth in computational modeling of emotion and cognitive-affective architectures occurred over the past 15 years. Emotion models and architectures are built to elucidate the mechanisms of emotions and enhance believability and effectiveness of synthetic agents and robots. Despite the many emotion models developed to date, a lack of consistency and clarity regarding what exactly it means to 'model emotions' persists. There are no systematic guidelines for development of computational models of emotions. This paper deconstructs the often vague term 'emotion modeling' by suggesting the view of emotion models in terms of two fundamental categories of processes: emotion generation and emotion effects. Computational tasks necessary to implement these processes are also identified. The paper addresses how computational building blocks provide a basis for the development of more systematic guidelines for affective model development. The paper concludes with a description of an affective requirements analysis and design process for developing affective computational models in agent architectures.