Implementing the dynamic role of mood and personality in emotion processing of cognitive agents

An ability to generate and express emotions constitutes an integral part of an artificial intelligent system be it cognitive architecture, virtual conversational agent or social robot. It is important to have an emotional component in those systems to enable the system to exhibit emotionally intelligent behaviour. This is in part achievable by integrating computational models of emotion into such cognitive systems. However, it is challenging to develop a computational model of emotion that embraces a wide range of cognitive aspects related to the process of emotion generation. As evident from the literature, mood and personality are the two aspects that are inseparable from the mechanism of emotion generation. In other words, mood and personality of an individual play a crucial role in determining the emotional state of an individual to a large extent. Thus, an emotion model that incorporates the notion of mood and personality is necessary to achieve a desirable level of emotional intelligence in cognitive systems. In this paper, we demonstrate how this integration has been achieved in our emotion model– EEGS. We also present how an artificial agent can show variation in emotion dynamics because of the influence of such factors, thus validating our theory.