Verification of Numeric Planning Problems through Domain Dynamic Consistency

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2 Citations (Scopus)


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 languageEnglish
Title of host publicationAIxIA 2022 – Advances in Artificial Intelligence
Subtitle of host publicationXXIst International Conference of the Italian Association for Artificial Intelligence, AIxIA 2022, Udine, Italy, November 28 – December 2, 2022, Proceedings
EditorsAgostino Dovier, Angelo Montanari, Andrea Orlandini
PublisherSpringer, Cham
Number of pages13
ISBN (Electronic)9783031271816
ISBN (Print)9783031271809
Publication statusPublished - 11 Mar 2023
Event21st International conference of the Italian association for Artificial Intelligence - University of Udine, Udine, Italy
Duration: 28 Nov 20222 Dec 2022
Conference number: 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13796 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference21st International conference of the Italian association for Artificial Intelligence
Abbreviated titleAIxIA 2022
Internet address


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