{"title":"系统理论与人工智能中的状态概念","authors":"J. Lunze","doi":"10.1049/ISE.1994.0021","DOIUrl":null,"url":null,"abstract":"The paper discusses the methodological analogies and differences of the systems theory and knowledge-based approaches to modelling and simulating dynamical systems. This comparison is based on the notion of the dynamical system as defined in systems theory, in particular on the concept of state. Two examples show that these notions are relevant for quantitative models as used in systems theory and for qualitative models given in the knowledge base of a rule-based system. In addition, a formalisation is provided of rule-based systems within the concept of dynamical systems. It shows that the main motivation for using the knowledge-based approach in control engineering is the lack of information about the state of the physical system.","PeriodicalId":55165,"journal":{"name":"Engineering Intelligent Systems for Electrical Engineering and Communications","volume":"49 1","pages":"201-210"},"PeriodicalIF":0.0000,"publicationDate":"1994-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Notion of the state in systems theory and artificial intelligence\",\"authors\":\"J. Lunze\",\"doi\":\"10.1049/ISE.1994.0021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper discusses the methodological analogies and differences of the systems theory and knowledge-based approaches to modelling and simulating dynamical systems. This comparison is based on the notion of the dynamical system as defined in systems theory, in particular on the concept of state. Two examples show that these notions are relevant for quantitative models as used in systems theory and for qualitative models given in the knowledge base of a rule-based system. In addition, a formalisation is provided of rule-based systems within the concept of dynamical systems. It shows that the main motivation for using the knowledge-based approach in control engineering is the lack of information about the state of the physical system.\",\"PeriodicalId\":55165,\"journal\":{\"name\":\"Engineering Intelligent Systems for Electrical Engineering and Communications\",\"volume\":\"49 1\",\"pages\":\"201-210\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Intelligent Systems for Electrical Engineering and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/ISE.1994.0021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Intelligent Systems for Electrical Engineering and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/ISE.1994.0021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Notion of the state in systems theory and artificial intelligence
The paper discusses the methodological analogies and differences of the systems theory and knowledge-based approaches to modelling and simulating dynamical systems. This comparison is based on the notion of the dynamical system as defined in systems theory, in particular on the concept of state. Two examples show that these notions are relevant for quantitative models as used in systems theory and for qualitative models given in the knowledge base of a rule-based system. In addition, a formalisation is provided of rule-based systems within the concept of dynamical systems. It shows that the main motivation for using the knowledge-based approach in control engineering is the lack of information about the state of the physical system.