Modelling social interactions between individuals for joint activity-travel scheduling

We describe a model of social activities, in which individuals negotiate about the type, purpose, location, and participants in activities. After participating in activities, individuals learn about new locations and acquaintances. Using theories from the activity-based modeling and social networks fields, a prototype model was created using Python incorporating utility-based agents who used a protocol to communicate with each other about potential activities in order to negotiate a suitable day and location. It can be shown that individuals with a large number of acquaintances participated in more activities. Pairs of individuals with high similarity values, based on age and gender, and with the same preferences for activities also socialized with each other more often. Future work involves more experimentation and eventual incorporation into activity-based models.