RT Journal Article
T1 A Self-Adaptive Evolutionary Approach to the Evolution of Aesthetic Maps for a RTS Game
A1 Lara-Cabrera, Raúl
A1 Cotta-Porras, Carlos
A1 Fernández-Leiva, Antonio José
K1 Inteligencia artificial
AB Procedural content generation (PCG) is a research  eld on the rise,with numerous papers devoted to this topic. This paper presents a PCGmethod 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 theirsubsequent evaluation: the sphere-of-inuence 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 tocapture the class of the map. A multiobjective evolutionary algorithm issubsequently employed to evolve maps, using these feature sets in order to measure distance to good (aesthetic) and bad (non-aesthetic) maps in thetraining set. The so-obtained results are visually analyzed and compared to the target maps using a Kohonen network.
YR 2014
FD 2014-04-22
LK http://hdl.handle.net/10630/7416
UL http://hdl.handle.net/10630/7416
LA eng
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026