Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation

Santiago Franco Aixela, Mauro Vallati, Alan Lindsay, Thomas McCluskey

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)


In the last decade, planning with domains modelled in the hybrid PDDL+ formalism has been gaining significant research interest. A number of approaches have been proposed that can handle PDDL+, and their exploitation fostered the use of planning in complex scenarios. In this paper we introduce a PDDL+ reformulation method that reduces
the size of the grounded problem, by reducing the arity of sparse predicates, i.e. predicates with a very large number of possible groundings, out of which very few are actually exploited in the planning problems. We include an empirical evaluation which demonstrates that these methods can substantially improve performance of domain-independent planners on PDDL+ domains.
Original languageEnglish
Title of host publicationComputational Science - ICCS 2019
Subtitle of host publication19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V
EditorsJoão M.F. Rodrigues, Pedro J.S. Cardoso, Jânio Monteiro, Roberto Lam, Valeria V. Krzhizhanovskaya, Michael H. Lees, Jack J. Dongarra, Peter M.A. Sloot
Place of PublicationCham
PublisherSpringer Verlag
Number of pages8
ISBN (Electronic)9783030227500
ISBN (Print)9783030227494, 3030227499
Publication statusPublished - 13 Aug 2019
Event19th International Conference on Computational Science - Faro, Portugal
Duration: 12 Jun 201914 Jun 2019
Conference number: 19

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Verlag
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Computational Science
Abbreviated titleICCS 2019
Internet address


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