{"title":"分布式知识库:自适应多智能体方法","authors":"J. S. Mertoguno","doi":"10.1109/IJSIS.1996.565054","DOIUrl":null,"url":null,"abstract":"This paper studies an approach of using multi-agents theory to construct an adaptive knowledge based system. To represent the knowledge, frame base (graph) knowledge representation has been chosen. The driving force of this study is the intention of having a distributed (possibly across the net) adaptive knowledge base. The challenge of developing an adaptive knowledge base depends on how to evolve the knowledge (adaptivity) and how to control the evolution (maintain the quality of the knowledge). In this paper the manifestation of both the issues discussed on our model is addressed.","PeriodicalId":437491,"journal":{"name":"Proceedings IEEE International Joint Symposia on Intelligence and Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Distributed knowledge-base: adaptive multi-agents approach\",\"authors\":\"J. S. Mertoguno\",\"doi\":\"10.1109/IJSIS.1996.565054\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies an approach of using multi-agents theory to construct an adaptive knowledge based system. To represent the knowledge, frame base (graph) knowledge representation has been chosen. The driving force of this study is the intention of having a distributed (possibly across the net) adaptive knowledge base. The challenge of developing an adaptive knowledge base depends on how to evolve the knowledge (adaptivity) and how to control the evolution (maintain the quality of the knowledge). In this paper the manifestation of both the issues discussed on our model is addressed.\",\"PeriodicalId\":437491,\"journal\":{\"name\":\"Proceedings IEEE International Joint Symposia on Intelligence and Systems\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Joint Symposia on Intelligence and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJSIS.1996.565054\",\"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 IEEE International Joint Symposia on Intelligence and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJSIS.1996.565054","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper studies an approach of using multi-agents theory to construct an adaptive knowledge based system. To represent the knowledge, frame base (graph) knowledge representation has been chosen. The driving force of this study is the intention of having a distributed (possibly across the net) adaptive knowledge base. The challenge of developing an adaptive knowledge base depends on how to evolve the knowledge (adaptivity) and how to control the evolution (maintain the quality of the knowledge). In this paper the manifestation of both the issues discussed on our model is addressed.