{"title":"进化主体自适应程度的模糊评价","authors":"I. Kallel, S. Mezghani, A. Alimi","doi":"10.1109/GEFS.2008.4484563","DOIUrl":null,"url":null,"abstract":"Referring to our readings about evolving and adaptive agents, we notice that most researchers proclaim the adaptivity of their systems' entities but without being able to estimate or evaluate it in a measure. Throughout this paper, we propose at first, to specify some crucial characteristics qualifying an entity (or agent) as evolving and adaptive. Since these characteristics are generally imperfect and suffer from uncertainties and inaccuracies, we propose a fuzzy rule base system (FRBS) as an intelligent method in order to estimate the measure of an adaptivity degree. We detail the fuzzy definition of selected inputs and output. Finally, we test and discuss the reliability of the suggested method on several examples, got from published works in various fields and had different characteristics.","PeriodicalId":343300,"journal":{"name":"2008 3rd International Workshop on Genetic and Evolving Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Towards a fuzzy evaluation of the adaptivity degree of an evolving agent\",\"authors\":\"I. Kallel, S. Mezghani, A. Alimi\",\"doi\":\"10.1109/GEFS.2008.4484563\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Referring to our readings about evolving and adaptive agents, we notice that most researchers proclaim the adaptivity of their systems' entities but without being able to estimate or evaluate it in a measure. Throughout this paper, we propose at first, to specify some crucial characteristics qualifying an entity (or agent) as evolving and adaptive. Since these characteristics are generally imperfect and suffer from uncertainties and inaccuracies, we propose a fuzzy rule base system (FRBS) as an intelligent method in order to estimate the measure of an adaptivity degree. We detail the fuzzy definition of selected inputs and output. Finally, we test and discuss the reliability of the suggested method on several examples, got from published works in various fields and had different characteristics.\",\"PeriodicalId\":343300,\"journal\":{\"name\":\"2008 3rd International Workshop on Genetic and Evolving Systems\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 3rd International Workshop on Genetic and Evolving Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GEFS.2008.4484563\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 3rd International Workshop on Genetic and Evolving Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GEFS.2008.4484563","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Towards a fuzzy evaluation of the adaptivity degree of an evolving agent
Referring to our readings about evolving and adaptive agents, we notice that most researchers proclaim the adaptivity of their systems' entities but without being able to estimate or evaluate it in a measure. Throughout this paper, we propose at first, to specify some crucial characteristics qualifying an entity (or agent) as evolving and adaptive. Since these characteristics are generally imperfect and suffer from uncertainties and inaccuracies, we propose a fuzzy rule base system (FRBS) as an intelligent method in order to estimate the measure of an adaptivity degree. We detail the fuzzy definition of selected inputs and output. Finally, we test and discuss the reliability of the suggested method on several examples, got from published works in various fields and had different characteristics.