Douglas Bonomo, Adrian P. Lauf, Roman V. Yampolskiy
{"title":"A crossword puzzle generator using genetic algorithms with Wisdom of Artificial Crowds","authors":"Douglas Bonomo, Adrian P. Lauf, Roman V. Yampolskiy","doi":"10.1109/CGames.2015.7272960","DOIUrl":null,"url":null,"abstract":"NP-hard problems, such as generating crossword puzzles, are candidates for solution by genetic algorithms (GAs). A combination of both a genetic algorithms and a Wisdom of Artificial Crowds (WoAC) aggregation method was developed for the purpose of creating crossword puzzles given a particular outline. The program was written using a GPL Hunspell wrapper NHunspell for word verification and suggestion. In American-style crossword puzzles, we saw performance improvements of around 20% in reaching a local optima, with a 6% improvement in the number of successful words found by a GA + WoAC algorithm over the baseline genetic algorithm.","PeriodicalId":447614,"journal":{"name":"2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CGames.2015.7272960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
NP-hard problems, such as generating crossword puzzles, are candidates for solution by genetic algorithms (GAs). A combination of both a genetic algorithms and a Wisdom of Artificial Crowds (WoAC) aggregation method was developed for the purpose of creating crossword puzzles given a particular outline. The program was written using a GPL Hunspell wrapper NHunspell for word verification and suggestion. In American-style crossword puzzles, we saw performance improvements of around 20% in reaching a local optima, with a 6% improvement in the number of successful words found by a GA + WoAC algorithm over the baseline genetic algorithm.