{"type":"ScholarlyArticle","title":"Reviving Partial Order Planning","authors":[{"name":"XuanLong Nguyen","slug":"xuanlong-nguyen","given":"XuanLong","family":"Nguyen","affiliation":""},{"name":"Subbarao Kambhampati","slug":"subbarao-kambhampati","given":"Subbarao","family":"Kambhampati","affiliation":""}],"abstract":"This paper challenges the prevailing pessimism about the scalability of partial order planning (POP) algorithms by presenting several novel heuristic control techniques that make them competitive with the state of the art plan synthesis algorithms. Our key insight is that the techniques responsible for the efficiency of the currently successful planners–viz., distance based heuristics, reachability analysis and disjunctive constraint handling–can also be adapted to dramatically improve the efficiency of the POP algorithm. We implement our ideas in a variant of UCPOP called R E POP1 . Our empirical results show that in addition to dominating UCPOP, R E POP also convincingly outperforms Graphplan in several “parallel” domains. The plans generated by R E POP also tend to be better than those generated by Graphplan and state search planners in terms of execution flexibility.","doi":null,"url":"https://ijcai.org/proceedings/2001/64","pdf":"https://ijcai.org/proceedings/2001/0064.pdf","markdown":"https://ijcai.org/proceedings/2001/64.md","bibtex":"https://ijcai.org/proceedings/2001/bibtex/64","volume":{"slug":"2001","title":"Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2001","url":"https://ijcai.org/proceedings/2001/","year":2001,"location":"Seattle, Washington, USA","dates":"","editors":"","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":64,"pages":{"first":459,"last":465},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}