{"title":"Petri网框架下的启发式搜索规划","authors":"K. Passino, P. Antsaklis","doi":"10.1109/ISIC.1988.65455","DOIUrl":null,"url":null,"abstract":"An artificial intelligence planning system's main components consist of a planner and a problem domain. The problem domain is the environment about which the planner reasons and on which it takes action. In the paper, a special type of extended input/output Petri net is defined and then used as the problem representation for a wide class of problem domains. A planning strategy is developed using results from the theory of heuristic search. In particular, using the developed Petri net framework and metric spaces, a class of heuristic functions that are both admissible and consistent for the A* algorithm is specified. The planning system architecture is discussed, and, as an illustration of the results, two simple planning problems are modeled and solved.<<ETX>>","PeriodicalId":155616,"journal":{"name":"Proceedings IEEE International Symposium on Intelligent Control 1988","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Planning via heuristic search in a Petri net framework\",\"authors\":\"K. Passino, P. Antsaklis\",\"doi\":\"10.1109/ISIC.1988.65455\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An artificial intelligence planning system's main components consist of a planner and a problem domain. The problem domain is the environment about which the planner reasons and on which it takes action. In the paper, a special type of extended input/output Petri net is defined and then used as the problem representation for a wide class of problem domains. A planning strategy is developed using results from the theory of heuristic search. In particular, using the developed Petri net framework and metric spaces, a class of heuristic functions that are both admissible and consistent for the A* algorithm is specified. The planning system architecture is discussed, and, as an illustration of the results, two simple planning problems are modeled and solved.<<ETX>>\",\"PeriodicalId\":155616,\"journal\":{\"name\":\"Proceedings IEEE International Symposium on Intelligent Control 1988\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1988-08-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings IEEE International Symposium on Intelligent Control 1988\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIC.1988.65455\",\"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 IEEE International Symposium on Intelligent Control 1988","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIC.1988.65455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Planning via heuristic search in a Petri net framework
An artificial intelligence planning system's main components consist of a planner and a problem domain. The problem domain is the environment about which the planner reasons and on which it takes action. In the paper, a special type of extended input/output Petri net is defined and then used as the problem representation for a wide class of problem domains. A planning strategy is developed using results from the theory of heuristic search. In particular, using the developed Petri net framework and metric spaces, a class of heuristic functions that are both admissible and consistent for the A* algorithm is specified. The planning system architecture is discussed, and, as an illustration of the results, two simple planning problems are modeled and solved.<>