Name
Title | ||
|---|---|---|
A methodology for designing emergent literary backstories on non-player characters using genetic algorithms |
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 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. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2598394.2598482 | GECCO (Companion) |
Keywords | Field | DocType |
content generation,genetic algorithms,literature,miscellaneous | Content generation,Computer science,Narrative,Archetype,Artificial intelligence,Genetic algorithm,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rubén Héctor García-Ortega | 1 | 6 | 1.81 |
| Pablo García-sánchez | 2 | 182 | 32.32 |
| Antonio Miguel Mora | 3 | 314 | 42.81 |
| Juan Julián Merelo Guervós | 4 | 483 | 75.75 |