{"title":"通过使用遗传算法发现图形类比","authors":"Henry Everett","doi":"10.1145/2817460.2817496","DOIUrl":null,"url":null,"abstract":"Researchers have studied graphic analogies from a wide range of disciplines and have perceived them in different ways. However, to represent analogy-making in computer simulations was not sought after until 1968 by a programmer by the name of Thomas Evans. His implementation was more or less a traditional way of viewing analogy-making decisions. The goal of my research is to first introduce an algorithm called Genetic Algorithm (GA) and from there give insight on how I went about developing a system that uses a GA to solve the analogy-making problem.","PeriodicalId":274966,"journal":{"name":"ACM-SE 35","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Discovering graphic analogies through the use of genetic algorithms\",\"authors\":\"Henry Everett\",\"doi\":\"10.1145/2817460.2817496\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Researchers have studied graphic analogies from a wide range of disciplines and have perceived them in different ways. However, to represent analogy-making in computer simulations was not sought after until 1968 by a programmer by the name of Thomas Evans. His implementation was more or less a traditional way of viewing analogy-making decisions. The goal of my research is to first introduce an algorithm called Genetic Algorithm (GA) and from there give insight on how I went about developing a system that uses a GA to solve the analogy-making problem.\",\"PeriodicalId\":274966,\"journal\":{\"name\":\"ACM-SE 35\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM-SE 35\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2817460.2817496\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM-SE 35","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2817460.2817496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Discovering graphic analogies through the use of genetic algorithms
Researchers have studied graphic analogies from a wide range of disciplines and have perceived them in different ways. However, to represent analogy-making in computer simulations was not sought after until 1968 by a programmer by the name of Thomas Evans. His implementation was more or less a traditional way of viewing analogy-making decisions. The goal of my research is to first introduce an algorithm called Genetic Algorithm (GA) and from there give insight on how I went about developing a system that uses a GA to solve the analogy-making problem.