{"title":"基于随机游走模型的模式适应度景观上位性研究","authors":"Jian-Wu Li, Min-Qiang Li","doi":"10.1109/ICMLC.2002.1167435","DOIUrl":null,"url":null,"abstract":"Interdependence between genes is an important factor causing hardness in genetic algorithms (GA). Traditional methods, which are used to measure the interaction between genes, can only reflect the extent of epistasis between all genes in the chromosome. In this paper, we propose the definition of the fitness landscape of schemata, and perform random walks on this landscape to study the degree of interdependence between some certain gene loci in study. According to the degree of interaction between these given gene loci, we can analyze and determine building blocks of GA. We also do a lot of experiments based on NK-models, and results of empirical analysis show that this method is effective.","PeriodicalId":90702,"journal":{"name":"Proceedings. International Conference on Machine Learning and Cybernetics","volume":"107 1","pages":"1396-1400 vol.3"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"The study of epistasis based on the random walk model in fitness landscapes of schemata\",\"authors\":\"Jian-Wu Li, Min-Qiang Li\",\"doi\":\"10.1109/ICMLC.2002.1167435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Interdependence between genes is an important factor causing hardness in genetic algorithms (GA). Traditional methods, which are used to measure the interaction between genes, can only reflect the extent of epistasis between all genes in the chromosome. In this paper, we propose the definition of the fitness landscape of schemata, and perform random walks on this landscape to study the degree of interdependence between some certain gene loci in study. According to the degree of interaction between these given gene loci, we can analyze and determine building blocks of GA. We also do a lot of experiments based on NK-models, and results of empirical analysis show that this method is effective.\",\"PeriodicalId\":90702,\"journal\":{\"name\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"volume\":\"107 1\",\"pages\":\"1396-1400 vol.3\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Machine Learning and Cybernetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMLC.2002.1167435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Machine Learning and Cybernetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMLC.2002.1167435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The study of epistasis based on the random walk model in fitness landscapes of schemata
Interdependence between genes is an important factor causing hardness in genetic algorithms (GA). Traditional methods, which are used to measure the interaction between genes, can only reflect the extent of epistasis between all genes in the chromosome. In this paper, we propose the definition of the fitness landscape of schemata, and perform random walks on this landscape to study the degree of interdependence between some certain gene loci in study. According to the degree of interaction between these given gene loci, we can analyze and determine building blocks of GA. We also do a lot of experiments based on NK-models, and results of empirical analysis show that this method is effective.