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dc.contributor.authorLara-Cabrera, Raúl
dc.contributor.authorCotta, Carlos 
dc.contributor.authorFernández-Leiva, Antonio José 
dc.date.accessioned2013-06-20T09:17:38Z
dc.date.available2013-06-20T09:17:38Z
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10630/5503
dc.description9th International Conference on Large Scale Scientific Computations. The final publication is available at link.springer.comes_ES
dc.description.abstractThis work presents a procedural content generation system that uses an evolutionary algorithm in order to generate interesting maps for a real-time strategy game, called Planet Wars. Interestingness is here captured by the dynamism of games (i.e., the extent to which they are action-packed). We consider two different approaches to measure the dynamism of the games resulting from these generated maps, one based on fluctuations in the resources controlled by either player and another one based on their confrontations. Both approaches rely on conducting several games on the map under scrutiny using top artificial intelligence (AI) bots for the game. Statistic gathered during these games are then transferred to a fuzzy system that determines the map's level of dynamism. We use an evolutionary algorithm featuring self-adaptation of mutation parameters and variable-length chromosomes (which means maps of different sizes) to produce increasingly dynamic maps.es_ES
dc.description.sponsorshipTIN2011-28627-C04-01, P10-TIC-6083es_ES
dc.language.isoenges_ES
dc.publisherSpringer-Verlages_ES
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectVideojuegoses_ES
dc.subjectAlgoritmos computacionaleses_ES
dc.subject.otherReal Time Strategyes_ES
dc.subject.otherProcedural Content Generationes_ES
dc.subject.otherEvolutionary Algorithmses_ES
dc.subject.otherSelf-Adaptationes_ES
dc.subject.otherPlanet Warses_ES
dc.titleUsing Self-Adaptive Evolutionary Algorithms to Evolve Dynamism-Oriented Maps for a Real Time Strategy Gamees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroE.T.S.I. Informáticaes_ES


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