{"title":"问题解决、分类和机器学习中的涌现","authors":"J. Quinqueton","doi":"10.1109/SYNASC.2006.37","DOIUrl":null,"url":null,"abstract":"Emergence is usually the way in which a collective organisation behaves differently than the sum of its elements. We propose here an overview of different ways this paradigm is used in several fields of artificial intelligence and we propose some theoretical tracks relying on some works in the field of machine learning","PeriodicalId":309740,"journal":{"name":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Emergence in Problem Solving, Classification and Machine Learning\",\"authors\":\"J. Quinqueton\",\"doi\":\"10.1109/SYNASC.2006.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emergence is usually the way in which a collective organisation behaves differently than the sum of its elements. We propose here an overview of different ways this paradigm is used in several fields of artificial intelligence and we propose some theoretical tracks relying on some works in the field of machine learning\",\"PeriodicalId\":309740,\"journal\":{\"name\":\"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SYNASC.2006.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SYNASC.2006.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Emergence in Problem Solving, Classification and Machine Learning
Emergence is usually the way in which a collective organisation behaves differently than the sum of its elements. We propose here an overview of different ways this paradigm is used in several fields of artificial intelligence and we propose some theoretical tracks relying on some works in the field of machine learning
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
