{"id":"https://openalex.org/W4391054849","doi":"https://doi.org/10.1145/3631085.3631324","title":"How to improve the quality of GAN-based map generators","display_name":"How to improve the quality of GAN-based map generators","publication_year":2023,"publication_date":"2023-11-06","ids":{"openalex":"https://openalex.org/W4391054849","doi":"https://doi.org/10.1145/3631085.3631324"},"language":"en","primary_location":{"id":"doi:10.1145/3631085.3631324","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3631085.3631324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd Brazilian Symposium on Games and Digital Entertainment","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010914659","display_name":"Daniele Fernandes E. Silva","orcid":"https://orcid.org/0009-0005-4802-2908"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]},{"id":"https://openalex.org/I4210147797","display_name":"Instituto Federal Farroupilha","ror":"https://ror.org/04eq71r04","country_code":"BR","type":"education","lineage":["https://openalex.org/I4210147797"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Daniele Fernandes E Silva","raw_affiliation_strings":[", Instituto Federal de Educa\u00e7\u00e3o, Ci\u00eancia e Tecnologia Farroupilha (IFFar), Brazil and Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas (UFPel), Brazil"],"raw_orcid":"https://orcid.org/0009-0005-4802-2908","affiliations":[{"raw_affiliation_string":", Instituto Federal de Educa\u00e7\u00e3o, Ci\u00eancia e Tecnologia Farroupilha (IFFar), Brazil and Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas (UFPel), Brazil","institution_ids":["https://openalex.org/I4210147797","https://openalex.org/I169248161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083634358","display_name":"Rafael Torchelsen","orcid":"https://orcid.org/0000-0003-2240-5183"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Rafael Piccin Torchelsen","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas (UFPel), Brazil"],"raw_orcid":"https://orcid.org/0000-0003-2240-5183","affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas (UFPel), Brazil","institution_ids":["https://openalex.org/I169248161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075071243","display_name":"Mar\u00edlton Sanchotene de Aguiar","orcid":"https://orcid.org/0000-0002-5247-6022"},"institutions":[{"id":"https://openalex.org/I169248161","display_name":"Universidade Federal de Pelotas","ror":"https://ror.org/05msy9z54","country_code":"BR","type":"education","lineage":["https://openalex.org/I169248161"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Marilton Sanchotene De Aguiar","raw_affiliation_strings":["Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas (UFPel), Brazil"],"raw_orcid":"https://orcid.org/0000-0002-5247-6022","affiliations":[{"raw_affiliation_string":"Programa de P\u00f3s-Gradua\u00e7\u00e3o em Computa\u00e7\u00e3o, Universidade Federal de Pelotas (UFPel), Brazil","institution_ids":["https://openalex.org/I169248161"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5010914659"],"corresponding_institution_ids":["https://openalex.org/I169248161","https://openalex.org/I4210147797"],"apc_list":null,"apc_paid":null,"fwci":0.3408,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.68146626,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11574","display_name":"Artificial Intelligence in Games","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8351526856422424},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6673348546028137},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6087734699249268},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.5626114010810852},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5335681438446045},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.532563328742981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5188035368919373},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.450514018535614},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.418676495552063},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3458086848258972},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3009345531463623},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.17757871747016907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8351526856422424},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6673348546028137},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6087734699249268},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.5626114010810852},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5335681438446045},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.532563328742981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5188035368919373},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.450514018535614},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.418676495552063},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3458086848258972},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3009345531463623},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.17757871747016907},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3631085.3631324","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3631085.3631324","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd Brazilian Symposium on Games and Digital Entertainment","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1976575031","https://openalex.org/W2125389028","https://openalex.org/W2604130399","https://openalex.org/W2605287558","https://openalex.org/W2785678896","https://openalex.org/W2811310411","https://openalex.org/W2962949934","https://openalex.org/W2963771763","https://openalex.org/W3007724674","https://openalex.org/W3093473164","https://openalex.org/W3094169176","https://openalex.org/W3096831136","https://openalex.org/W3117459900","https://openalex.org/W3126220825","https://openalex.org/W3168997536","https://openalex.org/W3194379089","https://openalex.org/W4287692716","https://openalex.org/W4295521014","https://openalex.org/W4296979096","https://openalex.org/W4298289240","https://openalex.org/W4385469643"],"related_works":["https://openalex.org/W2888032422","https://openalex.org/W2996316059","https://openalex.org/W4385421777","https://openalex.org/W3178813832","https://openalex.org/W4377980832","https://openalex.org/W2897769091","https://openalex.org/W2971552217","https://openalex.org/W3005996785","https://openalex.org/W4297411772","https://openalex.org/W4226298148"],"abstract_inverted_index":{"Procedural":[0],"Content":[1],"Generation":[2],"algorithms":[3],"aim":[4],"to":[5,25,75,92],"create":[6],"unique":[7],"and":[8,32,38,71,88],"variable":[9],"dungeon":[10,69],"maps,":[11],"ensuring":[12],"that":[13,97],"players":[14,30],"encounter":[15],"infinite":[16],"maps":[17,70,90,107],"in":[18,52,85],"the":[19,77],"game.":[20],"This":[21,61],"capability":[22],"is":[23],"essential":[24],"prevent":[26],"repetitive":[27],"environments,":[28],"keeping":[29],"engaged":[31],"providing":[33],"them":[34],"with":[35,108],"new":[36],"challenges":[37],"discoveries.":[39],"Machine":[40],"learning":[41],"techniques,":[42],"such":[43],"as":[44],"Generative":[45],"Adversarial":[46],"Networks":[47],"(GANs),":[48],"have":[49,58],"proven":[50],"effective":[51],"generating":[53,68,104],"data,":[54],"although":[55],"they":[56],"may":[57],"specific":[59],"limitations.":[60],"paper":[62],"proposes":[63],"a":[64],"GAN-based":[65],"approach":[66,81,99],"for":[67],"introduces":[72],"three":[73],"optimizations":[74],"enhance":[76],"training":[78],"process.":[79],"Our":[80],"achieves":[82],"remarkable":[83],"results":[84],"producing":[86],"valid":[87,106],"varied":[89],"compared":[91],"existing":[93],"methods.":[94],"We":[95],"demonstrate":[96],"our":[98],"outperforms":[100],"other":[101],"approaches":[102],"by":[103],"more":[105],"increased":[109],"variability.":[110]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}