{"title":"关于非单调传递关系的管理","authors":"B. Boutsinas","doi":"10.1109/TAI.1996.560479","DOIUrl":null,"url":null,"abstract":"Efficient representation of knowledge, under a multiple inheritance scheme with exceptions, plays an important role in artificial intelligence. Fast verification of the existence of a transitive relationship in such a hierarchy is of great importance. This paper presents an efficient algorithm for computing transitive relationships with exceptions. It is based on a known transitive closure compression technique that uses a labeled spanning tree of a directed acyclic graph. It is a very fast algorithm compared to graph-search algorithms that solve the same problem, without sacrificing some desirable properties that nonmonotonic multiple inheritance schemes should, in general, possess. Moreover it satisfies low storage requirements.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"On managing nonmonotonic transitive relationships\",\"authors\":\"B. Boutsinas\",\"doi\":\"10.1109/TAI.1996.560479\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficient representation of knowledge, under a multiple inheritance scheme with exceptions, plays an important role in artificial intelligence. Fast verification of the existence of a transitive relationship in such a hierarchy is of great importance. This paper presents an efficient algorithm for computing transitive relationships with exceptions. It is based on a known transitive closure compression technique that uses a labeled spanning tree of a directed acyclic graph. It is a very fast algorithm compared to graph-search algorithms that solve the same problem, without sacrificing some desirable properties that nonmonotonic multiple inheritance schemes should, in general, possess. Moreover it satisfies low storage requirements.\",\"PeriodicalId\":209171,\"journal\":{\"name\":\"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence\",\"volume\":\"76 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1996.560479\",\"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 Eighth IEEE International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1996.560479","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient representation of knowledge, under a multiple inheritance scheme with exceptions, plays an important role in artificial intelligence. Fast verification of the existence of a transitive relationship in such a hierarchy is of great importance. This paper presents an efficient algorithm for computing transitive relationships with exceptions. It is based on a known transitive closure compression technique that uses a labeled spanning tree of a directed acyclic graph. It is a very fast algorithm compared to graph-search algorithms that solve the same problem, without sacrificing some desirable properties that nonmonotonic multiple inheritance schemes should, in general, possess. Moreover it satisfies low storage requirements.