Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation

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

doi:10.1007/978-3-030-22750-0_42

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 proceeding › Conference contribution › peer-review

11 Citations (Scopus)

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.

Original language	English
Title of host publication	Computational Science - ICCS 2019
Subtitle of host publication	19th International Conference, Faro, Portugal, June 12–14, 2019, Proceedings, Part V
Editors	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
Place of Publication	Cham
Publisher	Springer Verlag
Pages	491-498
Number of pages	8
Volume	LNSC11540
Edition	1st
ISBN (Electronic)	9783030227500
ISBN (Print)	9783030227494, 3030227499
DOIs	https://doi.org/10.1007/978-3-030-22750-0_42
Publication status	Published - 13 Aug 2019
Event	19th International Conference on Computational Science - Faro, Portugal Duration: 12 Jun 2019 → 14 Jun 2019 Conference number: 19 https://www.iccs-meeting.org/iccs2019/

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Verlag
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference on Computational Science
Abbreviated title	ICCS 2019
Country/Territory	Portugal
City	Faro
Period	12/06/19 → 14/06/19
Internet address	https://www.iccs-meeting.org/iccs2019/

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ICCS_3Dto2DAccepted author manuscript, 252 KBLicence: Unspecified

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). Springer Verlag. https://doi.org/10.1007/978-3-030-22750-0_42

Franco Aixela, Santiago ; Vallati, Mauro ; Lindsay, Alan et al. / 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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title = "Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation",

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.",

keywords = "Automated Planning, Hybrid Reasoning, Reformulation",

author = "{Franco Aixela}, Santiago and Mauro Vallati and Alan Lindsay and Thomas McCluskey",

year = "2019",

month = aug,

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editor = "Rodrigues, {Jo{\~a}o M.F.} and Cardoso, {Pedro J.S.} and J{\^a}nio Monteiro and Roberto Lam and Krzhizhanovskaya, {Valeria V.} and Lees, {Michael H.} and Dongarra, {Jack J.} and Sloot, {Peter M.A.}",

booktitle = "Computational Science - ICCS 2019",

address = "Germany",

edition = "1st",

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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 et al.

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 proceeding › Conference contribution › peer-review

TY - GEN

T1 - Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation

AU - Franco Aixela, Santiago

AU - Vallati, Mauro

AU - Lindsay, Alan

AU - McCluskey, Thomas

N1 - Conference code: 19

PY - 2019/8/13

Y1 - 2019/8/13

N2 - 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.

AB - 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.

KW - Automated Planning

KW - Hybrid Reasoning

KW - Reformulation

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DO - 10.1007/978-3-030-22750-0_42

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SN - 9783030227494

SN - 3030227499

VL - LNSC11540

T3 - Lecture Notes in Computer Science

SP - 491

EP - 498

BT - Computational Science - ICCS 2019

A2 - Rodrigues, João M.F.

A2 - Cardoso, Pedro J.S.

A2 - Monteiro, Jânio

A2 - Lam, Roberto

A2 - Krzhizhanovskaya, Valeria V.

A2 - Lees, Michael H.

A2 - Dongarra, Jack J.

A2 - Sloot, Peter M.A.

PB - Springer Verlag

CY - Cham

T2 - 19th International Conference on Computational Science

Y2 - 12 June 2019 through 14 June 2019

ER -

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). Epub 2019 Jun 8. doi: 10.1007/978-3-030-22750-0_42

Improving Planning Performance in PDDL+ Domains via Automated Predicate Reformulation

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