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 contribution

Abstract

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.
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
Pages491-498
Number of pages8
VolumeLNSC11540
Edition1st
ISBN (Electronic)9783030227500
ISBN (Print)9783030227494, 3030227499
DOIs
Publication statusPublished - 13 Aug 2019
Event19th International Conference on Computational Science - Faro, Portugal
Duration: 12 Jun 201914 Jun 2019
https://www.iccs-meeting.org/iccs2019/

Publication series

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

Conference

Conference19th International Conference on Computational Science
Abbreviated titleICCS 2019
CountryPortugal
CityFaro
Period12/06/1914/06/19
Internet address

Fingerprint

Planning
Electric grounding

Cite this

Franco Aixela, S., Vallati, M., Lindsay, A., & McCluskey, T. (2019). Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation. In J. M. F. Rodrigues, P. J. S. Cardoso, J. Monteiro, R. Lam, V. V. Krzhizhanovskaya, M. H. Lees, J. J. Dongarra, ... P. M. A. Sloot (Eds.), Computational Science - ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V (1st ed., Vol. LNSC11540, pp. 491-498). (Lecture Notes in Computer Science). Cham: Springer Verlag. https://doi.org/10.1007/978-3-030-22750-0_42
Franco Aixela, Santiago ; Vallati, Mauro ; Lindsay, Alan ; McCluskey, Thomas. / Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation. Computational Science - ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V. editor / João M.F. Rodrigues ; Pedro J.S. Cardoso ; Jânio Monteiro ; Roberto Lam ; Valeria V. Krzhizhanovskaya ; Michael H. Lees ; Jack J. Dongarra ; Peter M.A. Sloot. Vol. LNSC11540 1st. ed. Cham : Springer Verlag, 2019. pp. 491-498 (Lecture Notes in Computer Science).
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abstract = "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 reducesthe 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.",
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Franco Aixela, S, Vallati, M, Lindsay, A & McCluskey, T 2019, Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation. in JMF Rodrigues, PJS Cardoso, J Monteiro, R Lam, VV Krzhizhanovskaya, MH Lees, JJ Dongarra & PMA Sloot (eds), Computational Science - ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V. 1st edn, vol. LNSC11540, Lecture Notes in Computer Science, Springer Verlag, Cham, pp. 491-498, 19th International Conference on Computational Science, Faro, Portugal, 12/06/19. https://doi.org/10.1007/978-3-030-22750-0_42

Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation. / Franco Aixela, Santiago; Vallati, Mauro; Lindsay, Alan; McCluskey, Thomas.

Computational Science - ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V. ed. / João M.F. Rodrigues; Pedro J.S. Cardoso; Jânio Monteiro; Roberto Lam; Valeria V. Krzhizhanovskaya; Michael H. Lees; Jack J. Dongarra; Peter M.A. Sloot. Vol. LNSC11540 1st. ed. Cham : Springer Verlag, 2019. p. 491-498 (Lecture Notes in Computer Science).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Franco Aixela S, Vallati M, Lindsay A, McCluskey T. Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation. In Rodrigues JMF, Cardoso PJS, Monteiro J, Lam R, Krzhizhanovskaya VV, Lees MH, Dongarra JJ, Sloot PMA, editors, Computational Science - ICCS 2019: 19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V. 1st ed. Vol. LNSC11540. Cham: Springer Verlag. 2019. p. 491-498. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-030-22750-0_42