A methodology for designing emergent literary backstories on non-player characters using genetic algorithms

The creation of fictional stories is a very complex task that usually implies a creative process where the author has to combine characters, conflicts and backstories to create an engaging narrative. This work presents a general methodology that uses individual based models to generate cohesive and coherent backstories where desired archetypes (universally accepted literary symbols) emerge and their life stories are a by-product of the simulation. This methodology includes the modeling and parameterization of the agents, the environment where they will live and the desired literary setting. The use of a genetic algorithm (GA) is proposed to establish the parameter configuration that will lead to backstories that best fit the setting. Information extracted from a simulation can then be used to create the backstories. To demonstrate the adequacy of the methodology, we perform an implementation using a specific multi-agent system and evaluate the results.