{"title":"离散事件模拟使用事件演算","authors":"Lode Missiaen","doi":"10.1109/TAI.1994.346449","DOIUrl":null,"url":null,"abstract":"This paper presents the theory and implementation of a logic based discrete event simulation system. The representation language of the simulation is Horn clause logic. The simulation's theory of time is based on event calculus. The scheduling algorithm generates event notices for all activities that can be performed. This logic approach to discrete event simulation facilitates model validation and maintenance. For a given event schedule, analysis can be done by deriving the properties that hold true of the world at any time in the situation history. This novel approach to simulation enables classical simulation to be extended with explanation generation, decision support, planning, inductive learning and simulation of intelligent agents.<<ETX>>","PeriodicalId":262014,"journal":{"name":"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Discrete event simulation using event calculus\",\"authors\":\"Lode Missiaen\",\"doi\":\"10.1109/TAI.1994.346449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents the theory and implementation of a logic based discrete event simulation system. The representation language of the simulation is Horn clause logic. The simulation's theory of time is based on event calculus. The scheduling algorithm generates event notices for all activities that can be performed. This logic approach to discrete event simulation facilitates model validation and maintenance. For a given event schedule, analysis can be done by deriving the properties that hold true of the world at any time in the situation history. This novel approach to simulation enables classical simulation to be extended with explanation generation, decision support, planning, inductive learning and simulation of intelligent agents.<<ETX>>\",\"PeriodicalId\":262014,\"journal\":{\"name\":\"Proceedings Sixth International Conference on Tools with Artificial Intelligence. TAI 94\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"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.1994.346449\",\"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.1994.346449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents the theory and implementation of a logic based discrete event simulation system. The representation language of the simulation is Horn clause logic. The simulation's theory of time is based on event calculus. The scheduling algorithm generates event notices for all activities that can be performed. This logic approach to discrete event simulation facilitates model validation and maintenance. For a given event schedule, analysis can be done by deriving the properties that hold true of the world at any time in the situation history. This novel approach to simulation enables classical simulation to be extended with explanation generation, decision support, planning, inductive learning and simulation of intelligent agents.<>