{"title":"规划和SAT","authors":"J. Rintanen","doi":"10.3233/978-1-58603-929-5-483","DOIUrl":null,"url":null,"abstract":"The planning problem in Artificial Intelligence was the first application of SAT to reasoning about transition systems and a direct precursor to the use of SAT in a number of other applications, including bounded model-checking in computer-aided verification. This chapter presents the main ideas about encoding goal reachability problems as a SAT problem, including parallel plans and different forms of constraints for speeding up SAT solving, as well as algorithms for solving the AI planning problem with a SAT solver. Finally, more general planning problems that require the use of QBF or other generalizations of SAT are discussed.","PeriodicalId":250589,"journal":{"name":"Handbook of Satisfiability","volume":"265 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"Planning and SAT\",\"authors\":\"J. Rintanen\",\"doi\":\"10.3233/978-1-58603-929-5-483\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The planning problem in Artificial Intelligence was the first application of SAT to reasoning about transition systems and a direct precursor to the use of SAT in a number of other applications, including bounded model-checking in computer-aided verification. This chapter presents the main ideas about encoding goal reachability problems as a SAT problem, including parallel plans and different forms of constraints for speeding up SAT solving, as well as algorithms for solving the AI planning problem with a SAT solver. Finally, more general planning problems that require the use of QBF or other generalizations of SAT are discussed.\",\"PeriodicalId\":250589,\"journal\":{\"name\":\"Handbook of Satisfiability\",\"volume\":\"265 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Handbook of Satisfiability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3233/978-1-58603-929-5-483\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Handbook of Satisfiability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/978-1-58603-929-5-483","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The planning problem in Artificial Intelligence was the first application of SAT to reasoning about transition systems and a direct precursor to the use of SAT in a number of other applications, including bounded model-checking in computer-aided verification. This chapter presents the main ideas about encoding goal reachability problems as a SAT problem, including parallel plans and different forms of constraints for speeding up SAT solving, as well as algorithms for solving the AI planning problem with a SAT solver. Finally, more general planning problems that require the use of QBF or other generalizations of SAT are discussed.