Sequence Pattern Mining for Citizens Behaviour Learning in Fair-Purpose Social Games. Some Preliminary Results

Abstract

Artificial Intelligence can be used to understand how citizens interact in a society with the aim to work together towards a better world. The application of AI in this domain has shown immense potential, particularly in leveraging games as powerful tools to simulate individual roles within a society. This research endeavors to explore how sequence pattern mining are applied to data coming from a game, in which humans are posed with the dilemma of progressing through their jobs, while enjoying life, trying to catch an equilibrium between happiness and healthiness. Preliminary results on a game played with 13 citizens shows the feasibility of sequence learning for this purpose. Our findings shed light on the intricate interplay of individual aspirations, communal synergies, and the pursuit of equilibrium, laying the foundation for future advancements in AI-driven methodologies for sociological investigations.