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Pruning Worlds into Stories: Affective Interactions as Fitness Function

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Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART 2024)

Abstract

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.

This paper has been partially funded by the projects CANTOR: Automated Composition of Personal Narratives as an aid for Occupational Therapy based on Reminescence, Grant. No. PID2019-108927RB-I00 (Spanish Ministry of Science and Innovation) and the ADARVE (Análisis de Datos de Realidad Virtual para Emergencias Radiológicas) Project funded by the Spanish Consejo de Seguridad Nuclear (CSN).

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Notes

  1. 1.

    Searches through outputs of the Bad News game required processing 140 years of simulation of a unique procedurally generated small American town [21].

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Correspondence to Pablo Gervás .

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Gervás, P., Méndez, G. (2024). Pruning Worlds into Stories: Affective Interactions as Fitness Function. In: Johnson, C., Rebelo, S.M., Santos, I. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2024. Lecture Notes in Computer Science, vol 14633. Springer, Cham. https://doi.org/10.1007/978-3-031-56992-0_12

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  • DOI: https://doi.org/10.1007/978-3-031-56992-0_12

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