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dc.contributor.authorAshlock, Daniel
dc.contributor.authorSalge, Christoph
dc.date.accessioned2020-03-21T01:02:04Z
dc.date.available2020-03-21T01:02:04Z
dc.date.issued2019-09-26
dc.identifier.citationAshlock , D & Salge , C 2019 , Automatic generation of level maps with the do what's possible representation . in IEEE Conference on Games 2019, CoG 2019 . , 8848032 , IEEE Conference on Computatonal Intelligence and Games, CIG , vol. 2019-August , IEEE Computer Society , 2019 IEEE Conference on Games, CoG 2019 , London , United Kingdom , 20/08/19 . https://doi.org/10.1109/CIG.2019.8848032
dc.identifier.citationconference
dc.identifier.isbn9781728118840
dc.identifier.issn2325-4270
dc.identifier.urihttp://hdl.handle.net/2299/22446
dc.description© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.description.abstractAutomatic generation of level maps is a popular form of automatic content generation. In this study, a recently developed technique employing the do what's possible representation is used to create open-ended level maps. Generation of the map can continue indefinitely, yielding a highly scalable representation. A parameter study is performed to find good parameters for the evolutionary algorithm used to locate high quality map generators. Variations on the technique are presented, demonstrating its versatility, and an algorithmic variant is given that both improves performance and changes the character of maps located. The ability of the map to adapt to different regions where the map is permitted to occupy space are also tested.en
dc.format.extent8
dc.format.extent224425
dc.language.isoeng
dc.publisherIEEE Computer Society
dc.relation.ispartofIEEE Conference on Games 2019, CoG 2019
dc.relation.ispartofseriesIEEE Conference on Computatonal Intelligence and Games, CIG
dc.subjectArtificial Intelligence
dc.subjectComputer Graphics and Computer-Aided Design
dc.subjectComputer Vision and Pattern Recognition
dc.subjectHuman-Computer Interaction
dc.subjectSoftware
dc.titleAutomatic generation of level maps with the do what's possible representationen
dc.contributor.institutionUniversity of Hertfordshire
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85073104977&partnerID=8YFLogxK
dc.identifier.urlhttps://arxiv.org/abs/1905.09618
rioxxterms.versionofrecord10.1109/CIG.2019.8848032
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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