Emerging archetypes in massive artificial societies for literary purposes using genetic algorithms

TL;DR

This paper demonstrates that complex literary archetypes can emerge in a simulated environment of artificial societies using genetic algorithms to optimize character profiles and parameters.

Contribution

It introduces a novel simulation environment and applies genetic algorithms to study the emergence of literary archetypes in artificial societies.

Findings

Archetypes like 'natality control' and 'revenge' can emerge naturally.

Parametrization of character profiles enables archetype emergence.

Genetic algorithms effectively optimize parameters for desired archetypes.

Abstract

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 plots to create an engaging narrative. This work presents a simulated environment with hundreds of characters that allows the study of coherent and interesting literary archetypes (or behaviours), plots and sub-plots. We will use this environment to perform a study about the number of profiles (parameters that define the personality of a character) needed to create two emergent scenes of archetypes: "natality control" and "revenge". A Genetic Algorithm (GA) will be used to find the fittest number of profiles and parameter configuration that enables the existence of the desired archetypes (played by the characters without their explicit knowledge). The results show that parametrizing this complex system is possible and that these kind of archetypes can emerge in the given environment.