This project simulates an urban environment where agents interact through conversations and their perception of the cityscape, influencing economic decisions and emotional states. Within a scenario defined by geographical boundaries and areas of interest, agents initiate dialogues that trigger changes in their routes, transportation methods, and overall behavior. Each conversation updates their emotions—reflected in environmental parameters—and influences choices such as decision adjustments and preference formations.
The system comprehensively maps the area using the H3 geospatial index, partitioning the territory into cells. Each cell is assigned amenities (POIs) extracted from the database, and from these, both a personality vector and an emotion vector are computed. These vectors are generated through weighted formulas that consider specific parameters for each POI, such as culinary diversity, the number of establishments, ratings, and the uniqueness of each area. This data integration enriches the context in which social interactions occur, enabling real-time modeling of collective behavior and providing a sophisticated perspective on urban dynamics.