{"type":"ScholarlyArticle","title":"A Refined Understanding of Cost-optimal Planning with Polytree Causal Graphs","authors":[{"name":"Christer Bäckström","slug":"christer-backstrom","given":"Christer","family":"Bäckström","affiliation":"Linköping University"},{"name":"Peter Jonsson","slug":"peter-jonsson","given":"Peter","family":"Jonsson","affiliation":"Linköping University"},{"name":"Sebastian Ordyniak","slug":"sebastian-ordyniak","given":"Sebastian","family":"Ordyniak","affiliation":"University of Sheffield"}],"abstract":"Complexity analysis based on the causal graphs of planning instances is a highly important research area. In particular, tractability results have led to new methods for constructing domain-independent heuristics. Important early examples of such results were presented by, for instance, Brafman & Domshlak and Katz & Keyder. More general results based on polytrees and bounding certain parameters were subsequently derived by Aghighi et al. and Ståhlberg. We continue this line of research by analyzing cost-optimal planning for instances with a polytree causal graph, bounded domain size and bounded depth. We show that no further restrictions are necessary for tractability, thus generalizing the previous results. Our approach is based on a novel method of closely analysing optimal plans: we recursively decompose the causal graph in a way that allows for bounding the number of variable changes as a function of the depth, using a reording argument and a comparison with prefix trees of known size. We then transform the planning instances into tree-structured constraint satisfaction instances.","doi":"10.24963/ijcai.2019/848","url":"https://ijcai.org/proceedings/2019/848","pdf":"https://ijcai.org/proceedings/2019/0848.pdf","markdown":"https://ijcai.org/proceedings/2019/848.md","bibtex":"https://ijcai.org/proceedings/2019/bibtex/848","volume":{"slug":"2019","title":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2019","url":"https://ijcai.org/proceedings/2019/","year":2019,"location":"Macao","dates":"10-16 August 2019","editors":"Sarit Kraus","isbn":"978-0-9992411-4-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2019"},"section":"Best Sister Conferences","track":"Best Sister Conferences","number":848,"pages":{"first":6126,"last":6130},"keywords":["Planning and Scheduling: Planning and Scheduling","Planning and Scheduling: Theoretical Foundations of Planning","Planning and Scheduling: Planning Algorithms"],"videos":[],"references":[{"position":1,"raw":"[Aghighi et al., 2015] Meysam Aghighi, Peter Jonsson, and Simon Ståhlberg. 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