{"type":"ScholarlyArticle","title":"Landmark Heuristics for Lifted Classical Planning","authors":[{"name":"Julia Wichlacz","slug":"julia-wichlacz","given":"Julia","family":"Wichlacz","affiliation":"Saarland University , Saarland Informatics Campus , Saarbrücken , Germany"},{"name":"Daniel Höller","slug":"daniel-holler","given":"Daniel","family":"Höller","affiliation":"Saarland University , Saarland Informatics Campus , Saarbrücken , Germany"},{"name":"Jörg Hoffmann","slug":"jorg-hoffmann","given":"Jörg","family":"Hoffmann","affiliation":"Saarland University , Saarland Informatics Campus , Saarbrücken , Germany"}],"abstract":"While state-of-the-art planning systems need a grounded (propositional) task representation, the input model is provided \"lifted\", specifying predicates and action schemas with variables over a finite object universe. The size of the grounded model is exponential in predicate/action-schema arity, limiting applicability to cases where it is small enough. Recent work has taken up this challenge, devising an effective lifted forward search planner as basis for lifted heuristic search, as well as a variety of lifted heuristic functions based on the delete relaxation. Here we add a novel family of lifted heuristic functions, based on landmarks. We design two methods for landmark extraction in the lifted setting. The resulting heuristics exhibit performance advantages over previous heuristics in several benchmark domains. Especially the combination with lifted delete relaxation heuristics to a LAMA-style planner yields good results, beating the previous state of the art in lifted planning.","doi":"10.24963/ijcai.2022/647","url":"https://ijcai.org/proceedings/2022/647","pdf":"https://ijcai.org/proceedings/2022/0647.pdf","markdown":"https://ijcai.org/proceedings/2022/647.md","bibtex":"https://ijcai.org/proceedings/2022/bibtex/647","volume":{"slug":"2022","title":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2022","url":"https://ijcai.org/proceedings/2022/","year":2022,"location":"Vienna","dates":"23-29 July 2022","editors":"Luc De Raedt","isbn":"978-1-956792-00-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2022"},"section":"Planning and Scheduling","track":"Main Track","number":647,"pages":{"first":4665,"last":4671},"keywords":["Planning and Scheduling: Planning Algorithms","Planning and Scheduling: Search in Planning and Scheduling"],"videos":[{"label":"Video #1","url":"https://slideslive.com/38986913","length_sec":89,"provider":"slideslive"},{"label":"Video #2","url":"https://slideslive.com/38985056","length_sec":314,"provider":"slideslive"}],"references":[{"position":1,"raw":"2: +at package_0 ?v2) (1: +in package_0 ?v1) (pick_up ?v1 ?v2 package_0 capacity_0 ?v3) (drop ?v1 ?v2 package_0 capacity_0 ?v4) (0: +at package_0 city_loc_1) (pick_up ?v1 city_loc_1 package_0 capacity_0 ?v5) References","title":"+in package_0 ?v1) (pick_up ?v1 ?v2 package_0 capacity_0 ?v3) (drop ?v1 ?v2 package_0 capacity_0 ?v4) (0: +at package_0 city_loc_1) (pick_up ?v1 city_loc_1 package_0 capacity_0 ?v5) References","authors":null,"year":null,"venue":null,"doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bonet and Geffner, 2001] Blai Bonet and Héctor Geffner. 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