Evolutionary Story Sifting over the Log of a Social Simulation

The process of selecting subsets out of a sequence of events on the grounds that told together they constitute an interesting narrative–known as story sifting–has become a topic of interest due to its applicability in video games that automatically develop large scale simulations of story worlds. Existing approaches to story sifting operate by matching subsequences of the available events onto patterns of plot considered to be of interest. The present paper proposes a two stage approach that combines a process of matching small strings of events connected by common sense relations–such as asking someone on a date and having them accept, or developing an attachment to someone who has given us a present–and an evolutionary search procedure that explores combinations of this type of paired events into longer sequences that constitute small plot lines about romantic entanglement. This procedure is run over the log of a multi-agent system that simulates a set of characters that develop a set of affective affinities between them as a result of social interactions of a romantic nature.