Verification of Numeric Planning Problems through Domain Dynamic Consistency

Enrico Scala; Lee McCluskey; Mauro Vallati

doi:10.1007/978-3-031-27181-6_12

Verification of Numeric Planning Problems through Domain Dynamic Consistency

Enrico Scala, Lee McCluskey, Mauro Vallati

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Verification of the development of complex problem models is an open problem in real-world applications of automated planning. To facilitate the verification task, this paper introduces the notion of Domain Dynamic Consistency for planning problems expressed in PDDL. This notion is aimed at signalling suspicious inputs arising at the intersection between the abstract description of the model and its concrete instantiation. Together with the notion we present an approximation based approach that is devoted to automatically solve the problem of deciding when a PDDL numeric planning problem is not Domain Dynamic Consistent. The paper terminates with an example of application of this notion and its related technique within a Urban Traffic Control scenario.

Original language	English
Title of host publication	AIxIA 2022 – Advances in Artificial Intelligence
Subtitle of host publication	XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings
Editors	Agostino Dovier, Angelo Montanari, Andrea Orlandini
Publisher	Springer, Cham
Pages	171-183
Number of pages	13
Edition	1st
ISBN (Electronic)	9783031271816
ISBN (Print)	9783031271809
DOIs	https://doi.org/10.1007/978-3-031-27181-6_12
Publication status	Published - 11 Mar 2023
Event	21st International conference of the Italian association for Artificial Intelligence - University of Udine, Udine, Italy Duration: 28 Nov 2022 → 2 Dec 2022 Conference number: 21 https://aixia2022.uniud.it/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13796 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	21st International conference of the Italian association for Artificial Intelligence
Abbreviated title	AIxIA 2022
Country/Territory	Italy
City	Udine
Period	28/11/22 → 2/12/22
Internet address	https://aixia2022.uniud.it/

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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aixia____DDCAccepted author manuscript, 309 KBLicence: Unspecified

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Scala, E., McCluskey, L., & Vallati, M. (2023). Verification of Numeric Planning Problems through Domain Dynamic Consistency. In A. Dovier, A. Montanari, & A. Orlandini (Eds.), AIxIA 2022 – Advances in Artificial Intelligence: XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings (1st ed., pp. 171-183). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13796 LNAI). Springer, Cham. https://doi.org/10.1007/978-3-031-27181-6_12

Scala, Enrico ; McCluskey, Lee ; Vallati, Mauro. / Verification of Numeric Planning Problems through Domain Dynamic Consistency. AIxIA 2022 – Advances in Artificial Intelligence: XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings. editor / Agostino Dovier ; Angelo Montanari ; Andrea Orlandini. 1st. ed. Springer, Cham, 2023. pp. 171-183 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Verification of Numeric Planning Problems through Domain Dynamic Consistency",

abstract = "Verification of the development of complex problem models is an open problem in real-world applications of automated planning. To facilitate the verification task, this paper introduces the notion of Domain Dynamic Consistency for planning problems expressed in PDDL. This notion is aimed at signalling suspicious inputs arising at the intersection between the abstract description of the model and its concrete instantiation. Together with the notion we present an approximation based approach that is devoted to automatically solve the problem of deciding when a PDDL numeric planning problem is not Domain Dynamic Consistent. The paper terminates with an example of application of this notion and its related technique within a Urban Traffic Control scenario.",

keywords = "Automated Planning, Numeric Planning, Verification",

author = "Enrico Scala and Lee McCluskey and Mauro Vallati",

note = "Funding Information: Acknowledgements. Mauro Vallati was supported by a UKRI Future Leaders Fellowship [grant number MR/T041196/1]. Enrico Scala has been partially supported by AIPlan4EU, a project funded by EU Horizon 2020 research and innovation programme under GA n. 101016442, and by the Italian MUR programme PRIN 2020, Prot.20203FFYLK (RIPER – Resilient AI-Based Self-Programming and Strategic Reasoning). Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 21st International conference of the Italian association for Artificial Intelligence, AIxIA 2022 ; Conference date: 28-11-2022 Through 02-12-2022",

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Scala, E, McCluskey, L & Vallati, M 2023, Verification of Numeric Planning Problems through Domain Dynamic Consistency. in A Dovier, A Montanari & A Orlandini (eds), AIxIA 2022 – Advances in Artificial Intelligence: XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings. 1st edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13796 LNAI, Springer, Cham, pp. 171-183, 21st International conference of the Italian association for Artificial Intelligence, Udine, Italy, 28/11/22. https://doi.org/10.1007/978-3-031-27181-6_12

Verification of Numeric Planning Problems through Domain Dynamic Consistency. / Scala, Enrico; McCluskey, Lee ; Vallati, Mauro.

AIxIA 2022 – Advances in Artificial Intelligence: XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings. ed. / Agostino Dovier; Angelo Montanari; Andrea Orlandini. 1st. ed. Springer, Cham, 2023. p. 171-183 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13796 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Verification of Numeric Planning Problems through Domain Dynamic Consistency

AU - Scala, Enrico

AU - McCluskey, Lee

AU - Vallati, Mauro

N1 - Conference code: 21

PY - 2023/3/11

Y1 - 2023/3/11

N2 - Verification of the development of complex problem models is an open problem in real-world applications of automated planning. To facilitate the verification task, this paper introduces the notion of Domain Dynamic Consistency for planning problems expressed in PDDL. This notion is aimed at signalling suspicious inputs arising at the intersection between the abstract description of the model and its concrete instantiation. Together with the notion we present an approximation based approach that is devoted to automatically solve the problem of deciding when a PDDL numeric planning problem is not Domain Dynamic Consistent. The paper terminates with an example of application of this notion and its related technique within a Urban Traffic Control scenario.

AB - Verification of the development of complex problem models is an open problem in real-world applications of automated planning. To facilitate the verification task, this paper introduces the notion of Domain Dynamic Consistency for planning problems expressed in PDDL. This notion is aimed at signalling suspicious inputs arising at the intersection between the abstract description of the model and its concrete instantiation. Together with the notion we present an approximation based approach that is devoted to automatically solve the problem of deciding when a PDDL numeric planning problem is not Domain Dynamic Consistent. The paper terminates with an example of application of this notion and its related technique within a Urban Traffic Control scenario.

KW - Automated Planning

KW - Numeric Planning

KW - Verification

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DO - 10.1007/978-3-031-27181-6_12

M3 - Conference contribution

SN - 9783031271809

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 171

EP - 183

BT - AIxIA 2022 – Advances in Artificial Intelligence

A2 - Dovier, Agostino

A2 - Montanari, Angelo

A2 - Orlandini, Andrea

PB - Springer, Cham

T2 - 21st International conference of the Italian association for Artificial Intelligence

Y2 - 28 November 2022 through 2 December 2022

ER -

Scala E, McCluskey L , Vallati M. Verification of Numeric Planning Problems through Domain Dynamic Consistency. In Dovier A, Montanari A, Orlandini A, editors, AIxIA 2022 – Advances in Artificial Intelligence: XXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings. 1st ed. Springer, Cham. 2023. p. 171-183. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2023 Mar 10. doi: 10.1007/978-3-031-27181-6_12

Verification of Numeric Planning Problems through Domain Dynamic Consistency

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