{"type":"ScholarlyArticle","title":"Automatic SAT-Compilation of Planning Problems","authors":[{"name":"Michael D. Ernst","slug":"michael-d-ernst","given":"Michael D.","family":"Ernst","affiliation":""},{"name":"Todd D. Millstein","slug":"todd-d-millstein","given":"Todd D.","family":"Millstein","affiliation":""},{"name":"Daniel S. Weld","slug":"daniel-s-weld","given":"Daniel S.","family":"Weld","affiliation":""}],"abstract":"Recent work by Kautz et al. provides tantalizing evidence that large, classical planning problems may be efficiently solved by translating them into propositional satisfiability problems, using stochastic search techniques , and translating the resulting truth assignments back into plans for the original problems. We explore the space of such transformations , providing a simple framework that generates eight major encodings (generated by selecting one of four action representations and one of two frame axioms) and a number of subsidiary ones. We describe a fully-implemented compiler that can generate each of these encodings, and we test the compiler on a suite of STRIPS planning problems in order to determine which encodings have the best properties.","doi":null,"url":"https://ijcai.org/proceedings/1997/169","pdf":"https://ijcai.org/proceedings/1997/0169.pdf","markdown":"https://ijcai.org/proceedings/1997/169.md","bibtex":"https://ijcai.org/proceedings/1997/bibtex/169","volume":{"slug":"1997","title":"Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1997","url":"https://ijcai.org/proceedings/1997/","year":1997,"location":"Nagoya, Japan","dates":"","editors":"Martha E. Pollack","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Planning and Scheduling","track":"Planning and Scheduling","number":169,"pages":{"first":1169,"last":1176},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}