{"title":"一种实时异步生产系统中的知识表示、验证和推理方案","authors":"T. S. Perraju, G. Uma, B. E. Prasad","doi":"10.1109/TAI.1994.346433","DOIUrl":null,"url":null,"abstract":"Expert systems for real time process monitoring need to respond to asynchronous events and reason about temporal properties of the process. This requires the ability to perform data input, event handling and temporal asynchronous reasoning during the inference cycle. Conventional expert systems do not possess these abilities. We describe a knowledge representation formalism which captures dynamic properties like external events, timing constraints and data trends in addition to diagnostic knowledge. This representation lends itself to verification of the knowledge base. We further show the implementation of a multiple rule firing asynchronous inference engine using this model.<<ETX>>","PeriodicalId":262014,"journal":{"name":"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A scheme for knowledge representation, verification and reasoning in real time asynchronous production systems\",\"authors\":\"T. S. Perraju, G. Uma, B. E. Prasad\",\"doi\":\"10.1109/TAI.1994.346433\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Expert systems for real time process monitoring need to respond to asynchronous events and reason about temporal properties of the process. This requires the ability to perform data input, event handling and temporal asynchronous reasoning during the inference cycle. Conventional expert systems do not possess these abilities. We describe a knowledge representation formalism which captures dynamic properties like external events, timing constraints and data trends in addition to diagnostic knowledge. This representation lends itself to verification of the knowledge base. We further show the implementation of a multiple rule firing asynchronous inference engine using this model.<<ETX>>\",\"PeriodicalId\":262014,\"journal\":{\"name\":\"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1994.346433\",\"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 Sixth International Conference on Tools with Artificial Intelligence. TAI 94","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1994.346433","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A scheme for knowledge representation, verification and reasoning in real time asynchronous production systems
Expert systems for real time process monitoring need to respond to asynchronous events and reason about temporal properties of the process. This requires the ability to perform data input, event handling and temporal asynchronous reasoning during the inference cycle. Conventional expert systems do not possess these abilities. We describe a knowledge representation formalism which captures dynamic properties like external events, timing constraints and data trends in addition to diagnostic knowledge. This representation lends itself to verification of the knowledge base. We further show the implementation of a multiple rule firing asynchronous inference engine using this model.<>