{"title":"加速懒惰基础答案集解决","authors":"Richard Comploi-Taupe","doi":"10.4230/OASIcs.ICLP.2018.20","DOIUrl":null,"url":null,"abstract":"The grounding bottleneck is an important open issue in Answer Set Programming. Lazy grounding addresses it by interleaving grounding and search. The performance of current lazy-grounding solvers is not yet comparable to that of ground-and-solve systems, however. The aim of this thesis is to extend prior work on lazy grounding by novel heuristics and other techniques like non-ground conflict learning in order to speed up solving. Parts of expected results will be beneficial for ground-and-solve systems as well.","PeriodicalId":271041,"journal":{"name":"International Conference on Logic Programming","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Speeding up Lazy-Grounding Answer Set Solving\",\"authors\":\"Richard Comploi-Taupe\",\"doi\":\"10.4230/OASIcs.ICLP.2018.20\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The grounding bottleneck is an important open issue in Answer Set Programming. Lazy grounding addresses it by interleaving grounding and search. The performance of current lazy-grounding solvers is not yet comparable to that of ground-and-solve systems, however. The aim of this thesis is to extend prior work on lazy grounding by novel heuristics and other techniques like non-ground conflict learning in order to speed up solving. Parts of expected results will be beneficial for ground-and-solve systems as well.\",\"PeriodicalId\":271041,\"journal\":{\"name\":\"International Conference on Logic Programming\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Logic Programming\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4230/OASIcs.ICLP.2018.20\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Logic Programming","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4230/OASIcs.ICLP.2018.20","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The grounding bottleneck is an important open issue in Answer Set Programming. Lazy grounding addresses it by interleaving grounding and search. The performance of current lazy-grounding solvers is not yet comparable to that of ground-and-solve systems, however. The aim of this thesis is to extend prior work on lazy grounding by novel heuristics and other techniques like non-ground conflict learning in order to speed up solving. Parts of expected results will be beneficial for ground-and-solve systems as well.