Pruning Worlds into Stories: Affective Interactions as Fitness Function

An important challenge when trying to find a story to tell about some set of events that has already happened is to identify the elements in that set of events that will make a story that moves the intended audience. One possible criterion is to consider events that involve significant changes in the emotional relations between the characters involved. The present paper explores a computational model of this particular approach to the task of storytelling. An evolutionary solution is used to explore the logs of an agent-based social simulation, using metrics on the evolution of affinity between characters as fitness function, to identify sequences of events that might be good candidates for moving stories.