Lifted Fact-Alternating Mutex Groups and Pruned Grounding of Classical Planning Problems

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

25 Citations (Scopus)

Abstract

In this paper, we focus on the inference of mutex groups in the lifted (PDDL) representation. We formalize the inference and prove that the most commonly used translator from the Fast Downward (FD) planning system infers a certain subclass of mutex groups, called fact-alternating mutex groups (fam-groups). Based on that, we show that the previously proposed fam-groups-based pruning techniques for the STRIPS representation can be utilized during the grounding process with lifted fam-groups, i.e., before the full STRIPS representation is known. Furthermore, we propose an improved inference algorithm for lifted fam-groups that produces a richer set of fam-groups than the FD translator and we demonstrate a positive impact on the number of pruned operators and overall coverage.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI-20
Number of pages8
Publication date3 Apr 2020
Pages9835-9842
DOIs
Publication statusPublished - 3 Apr 2020
Externally publishedYes
Event34th AAAI Conference on Artificial Intelligence, AAAI 2020 - New York, United States
Duration: 7 Feb 202012 Feb 2020

Conference

Conference34th AAAI Conference on Artificial Intelligence, AAAI 2020
Country/TerritoryUnited States
CityNew York
Period07/02/202012/02/2020
SponsorAssociation for the Advancement of Artificial Intelligence

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