Evolutionary Generation of Game Levels

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aut.relation.endpagee4
aut.relation.issue15en_NZ
aut.relation.journalEAI Endorsed Transactions on Creative Technologiesen_NZ
aut.relation.startpagee4
aut.relation.volume5en_NZ
aut.researcherConnor, Andrew
dc.contributor.authorConnor, AMen_NZ
dc.contributor.authorGreig, TJen_NZ
dc.contributor.authorKruse, Jen_NZ
dc.date.accessioned2018-10-30T23:54:18Z
dc.date.available2018-10-30T23:54:18Z
dc.date.copyright2018en_NZ
dc.date.issued2018en_NZ
dc.description.abstractThis paper outlines an approach for evolutionary procedural generation of video game content. The study deals with the automatic generation of game level designs using genetic algorithms and the development of a fitness function that describes the playability of the game level. The research explores whether genetic algorithms have the ability to produce outcomes that demonstrate characteristics that arise through human creativity, and whether these automated approaches offer any benefits in terms of time and effort involved in the design process. The approach is compared to a random method and the results show that the genetic algorithm is more consistent in finding levels; however analysis of the game levels indicates that the fitness function is not fully capturing level playability. The ability to produce playable levels decreases as the play area increases, however there is potential to produce larger maps that are both playable and arguably creative through a recombination method.
dc.identifier.citationEAI Endorsed Transactions on Creative Technologies, ct 18(15): e4, doi: 10.4108/eai.10-4-2018.155857
dc.identifier.doi10.4108/eai.10-4-2018.155857en_NZ
dc.identifier.issn2409-9708en_NZ
dc.identifier.urihttps://hdl.handle.net/10292/11917
dc.publisherInstitute for Computer Sciences, Social Informatics and Telecommunications Engineering (ICST)en_NZ
dc.relation.urihttp://eudl.eu/doi/10.4108/eai.10-4-2018.155857
dc.rightsCopyright © 2018 A.M. Connor et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
dc.rights.accessrightsOpenAccessen_NZ
dc.subjectProcedural Content Generation; Creative Computing; Novelty Generation; Video Game Design; Genetic Algorithms; Computational Creativity
dc.titleEvolutionary Generation of Game Levelsen_NZ
dc.typeJournal Article
pubs.elements-id279337
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/Design & Creative Technologies/Art & Design
pubs.organisational-data/AUT/Design & Creative Technologies/CoLab
pubs.organisational-data/AUT/PBRF
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF Art and Design
pubs.organisational-data/AUT/PBRF/PBRF Design and Creative Technologies/PBRF CoLab
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