The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis On a Real-World Case Study

Anas  El Kouaiti; Francesco Percassi; Alessandro Saetti; Mauro Vallati

The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis On a Real-World Case Study

Anas El Kouaiti, Francesco Percassi, Alessandro Saetti, Mauro Vallati

Research output: Contribution to journal › Conference article › peer-review

Abstract

PDDL+ is an expressive formalism that allows for the use of planning in complex real-world applications. It includes a number of features designed to improve the readability and conciseness of the resulting knowledge models, but that are commonly doubted to have detrimental impact on the performance of domain-independent searches and heuristics. In this paper we empirically assess the impact of such features in a challenging real-world case study.

Original language	English
Article number	135326
Number of pages	3
Journal	Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS
Volume	37
Publication status	Published - 12 May 2024
Event	37th International FLAIRS Conference - Hilton Sandestin Beach Golf Resort and Spa, Miramar Beach, Miramar Beach, United States Duration: 19 May 2024 → 21 May 2024 Conference number: 37 https://www.flairs-37.info/

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https://journals.flvc.org/FLAIRS/article/view/135326Licence: CC BY-NC

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title = "The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis On a Real-World Case Study",

abstract = "PDDL+ is an expressive formalism that allows for the use of planning in complex real-world applications. It includes a number of features designed to improve the readability and conciseness of the resulting knowledge models, but that are commonly doubted to have detrimental impact on the performance of domain-independent searches and heuristics. In this paper we empirically assess the impact of such features in a challenging real-world case study.",

keywords = "PDDL+, planning performance, automated planning",

author = "\{El Kouaiti\}, Anas and Francesco Percassi and Alessandro Saetti and Mauro Vallati",

note = "Funding Information: Francesco Percassi and Mauro Vallati were supported by a UKRI Future Leaders Fellowship [grant number MR/T041196/1]. Publisher Copyright: Copyright {\textcopyright} 2024 by the authors.; 37th International FLAIRS Conference, FLAIRS 2024 ; Conference date: 19-05-2024 Through 21-05-2024",

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journal = "Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS",

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The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis On a Real-World Case Study. / El Kouaiti, Anas ; Percassi, Francesco; Saetti, Alessandro et al.
In: Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS, Vol. 37, 135326, 12.05.2024.

Research output: Contribution to journal › Conference article › peer-review

TY - JOUR

T1 - The Impact of PDDL+ Language Features on Planning Performance

T2 - 37th International FLAIRS Conference

AU - El Kouaiti, Anas

AU - Percassi, Francesco

AU - Saetti, Alessandro

AU - Vallati, Mauro

N1 - Conference code: 37

PY - 2024/5/12

Y1 - 2024/5/12

N2 - PDDL+ is an expressive formalism that allows for the use of planning in complex real-world applications. It includes a number of features designed to improve the readability and conciseness of the resulting knowledge models, but that are commonly doubted to have detrimental impact on the performance of domain-independent searches and heuristics. In this paper we empirically assess the impact of such features in a challenging real-world case study.

AB - PDDL+ is an expressive formalism that allows for the use of planning in complex real-world applications. It includes a number of features designed to improve the readability and conciseness of the resulting knowledge models, but that are commonly doubted to have detrimental impact on the performance of domain-independent searches and heuristics. In this paper we empirically assess the impact of such features in a challenging real-world case study.

KW - PDDL+

KW - planning performance

KW - automated planning

UR - https://doi.org/10.32473/flairs.37

UR - https://www.scopus.com/pages/publications/85200486190

M3 - Conference article

SN - 2334-0754

VL - 37

JO - Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS

JF - Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS

M1 - 135326

Y2 - 19 May 2024 through 21 May 2024

ER -

The Impact of PDDL+ Language Features on Planning Performance: An Empirical Analysis On a Real-World Case Study

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