{"title":"应用元推理将CBR和BN相结合","authors":"T. Houeland, Tore Bruland, A. Aamodt, H. Langseth","doi":"10.3233/978-1-60750-754-3-189","DOIUrl":null,"url":null,"abstract":"In complex domains, it is often necessary to determine which reasoning method would be the most appropriate for each task, and a combination of different methods has often shown the best results. We examine how two complementary reasoning methods, case-based reasoning and Bayesian networks, can be combined using metareasoning to form a more robust and better-performing system.","PeriodicalId":322432,"journal":{"name":"Scandinavian Conference on AI","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Extended Abstract: Combining CBR and BN using metareasoning\",\"authors\":\"T. Houeland, Tore Bruland, A. Aamodt, H. Langseth\",\"doi\":\"10.3233/978-1-60750-754-3-189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In complex domains, it is often necessary to determine which reasoning method would be the most appropriate for each task, and a combination of different methods has often shown the best results. We examine how two complementary reasoning methods, case-based reasoning and Bayesian networks, can be combined using metareasoning to form a more robust and better-performing system.\",\"PeriodicalId\":322432,\"journal\":{\"name\":\"Scandinavian Conference on AI\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scandinavian Conference on AI\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/978-1-60750-754-3-189\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scandinavian Conference on AI","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/978-1-60750-754-3-189","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extended Abstract: Combining CBR and BN using metareasoning
In complex domains, it is often necessary to determine which reasoning method would be the most appropriate for each task, and a combination of different methods has often shown the best results. We examine how two complementary reasoning methods, case-based reasoning and Bayesian networks, can be combined using metareasoning to form a more robust and better-performing system.