2026-06-01T06:56:20Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/108852026-02-03T12:09:36Zcom_10630_2254col_10630_37959
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Lara-Cabrera, Raúl
author
Gutiérrez-Alcoba, Alejandro
author
Fernández-Leiva, Antonio José
2016-01-18T08:38:07Z
2016-01-18T08:38:07Z
2016-01-18
http://hdl.handle.net/10630/10885
http://orcid.org/0000-0002-5330-5217
This paper presents a spatially-structured evolutionary algorithm (EA) to procedurally generate game maps of di ferent levels of di ficulty to be solved, in Gravityvolve!, a physics-based simulation videogame that we have implemented and which is inspired by the n-
body problem, a classical problem in the fi eld of physics and mathematics. The proposal consists of a steady-state EA whose population is partitioned into three groups according to the di ficulty of the generated content (hard, medium or easy) which can be easily adapted to handle the automatic creation of content of diverse nature in other games. In addition, we present three fitness functions, based on multiple criteria (i.e:, intersections, gravitational acceleration and simulations), that were used experimentally to conduct the search process for creating a database of
maps with di ferent di ficulty in Gravityvolve!.
eng
by-nc-nd
Computación evolutiva
A spatially-structured PCG method for content diversity in a Physics-based simulation game
conference output
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URL
https://riuma.uma.es/bitstreams/ac9ba944-c690-4c7b-afc7-bab963b55373/download
File
MD5
b66afca220034aef69929de81d9811e4
2408253
application/pdf
Lara-Cabrera.pdf