2026-06-02T00:53:20Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/74162026-02-03T11:26:25Zcom_10630_2254col_10630_37953
RIUMA. Repositorio Institucional de la Universidad de Málaga
author
Lara-Cabrera, Raúl
author
Cotta-Porras, Carlos
author
Fernández-Leiva, Antonio José
2014-04-22T09:34:40Z
2014-04-22T09:34:40Z
2014-04-22
http://hdl.handle.net/10630/7416
Procedural content generation (PCG) is a research eld on the rise,with numerous papers devoted to this topic. This paper presents a PCG
method based on a self-adaptive evolution strategy for the automatic generation of maps for the real-time strategy (RTS) game PlanetWars. These maps are generated in order to ful ll the aesthetic preferences of the user, as implied by her assessment of a collection of maps used as training set. A topological approach is used for the characterization of the maps and their
subsequent evaluation: the sphere-of-in
uence graph (SIG) of each map is built, several graph-theoretic measures are computed on it, and a feature selection method is utilized to determine adequate subsets of measures to
capture the class of the map. A multiobjective evolutionary algorithm is
subsequently employed to evolve maps, using these feature sets in order to measure distance to good (aesthetic) and bad (non-aesthetic) maps in the
training set. The so-obtained results are visually analyzed and compared to the target maps using a Kohonen network.
eng
Inteligencia artificial
A Self-Adaptive Evolutionary Approach to the Evolution of Aesthetic Maps for a RTS Game
journal article
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