{"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}
引用次数: 21
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.<>