基于遗传学的专家系统规则库自动获取技术

[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs Pub Date : 1991-09-30 DOI:10.1109/DMESP.1991.171705

Clayton M. Johnson, Stefan Feyock

{"title":"基于遗传学的专家系统规则库自动获取技术","authors":"Clayton M. Johnson, Stefan Feyock","doi":"10.1109/DMESP.1991.171705","DOIUrl":null,"url":null,"abstract":"The genetic algorithm (GA) is a powerful search paradigm which combines elements from evolutionary biology with concepts from population genetics. Because they operate in a domain-independent fashion, GAs have been successfully applied to a wide variety of optimization and learning problems. A technique is presented by which genetic algorithms can be adapted to operate upon the LISP-like production rules typically used in expert systems. A brief overview is presented of genetic algorithms and genetics-based learning.<<ETX>>","PeriodicalId":117336,"journal":{"name":"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs","volume":"186 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"A genetics-based technique for the automated acquisition of expert system rule bases\",\"authors\":\"Clayton M. Johnson, Stefan Feyock\",\"doi\":\"10.1109/DMESP.1991.171705\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The genetic algorithm (GA) is a powerful search paradigm which combines elements from evolutionary biology with concepts from population genetics. Because they operate in a domain-independent fashion, GAs have been successfully applied to a wide variety of optimization and learning problems. A technique is presented by which genetic algorithms can be adapted to operate upon the LISP-like production rules typically used in expert systems. A brief overview is presented of genetic algorithms and genetics-based learning.<<ETX>>\",\"PeriodicalId\":117336,\"journal\":{\"name\":\"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs\",\"volume\":\"186 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DMESP.1991.171705\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DMESP.1991.171705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 8

摘要

遗传算法(GA)是一种强大的搜索范式，它结合了进化生物学的元素和群体遗传学的概念。由于GAs以领域独立的方式运行，因此已成功地应用于各种优化和学习问题。提出了一种技术，通过这种技术，遗传算法可以适应于在专家系统中通常使用的类似lisp的生产规则上进行操作。简要概述了遗传算法和基于遗传的学习。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A genetics-based technique for the automated acquisition of expert system rule bases

The genetic algorithm (GA) is a powerful search paradigm which combines elements from evolutionary biology with concepts from population genetics. Because they operate in a domain-independent fashion, GAs have been successfully applied to a wide variety of optimization and learning problems. A technique is presented by which genetic algorithms can be adapted to operate upon the LISP-like production rules typically used in expert systems. A brief overview is presented of genetic algorithms and genetics-based learning.<>

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

[1991] Proceedings of the IEEE/ACM International Conference on Developing and Managing Expert System Programs

自引率

0.00%

发文量