TOWARDS A COMPANION ROBOT: A COGNITIVE AGENT MODEL OF THE DYNAMICS OF LONELINESS

Loneliness is a prevalent and global problem for all people, and it can adversely affect their quality of life. Many research investigations have confirmed the negative psychological impacts of loneliness on people’s the unwanted impact of loneliness. Yet, these interventions are missing the power of reasoning to predict the onset of loneliness. Consequently, this paper presented the work of developing a computational cognitive agent model of loneliness using a causal networking modeling approach by relying on discrepancy model as a benchmark to serve as analytics engine for a companion robot design. Loneliness determinants and their causal relationships were identified from the literature and formalized to construct the intended cognitive agent model. Furthermore, simulation analyses under various parameter settings were implemented to explore the causal relationships among the identified loneliness determinants and those simulations revealed similar behaviors or patterns to existing literature. The designed cognitive agent model was evaluated using both of mathematical analysis and automated logical analysis. These two evaluation approaches have proved the correctness of the designed model. The developed computational loneliness agent model with little tuning can serve as a core analytical engine for intelligent technologies such as robots to control and monitor the adverse effects of loneliness