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Verification of Numeric Planning Problems Through Domain Dynamic Consistency

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AIxIA 2022 – Advances in Artificial Intelligence (AIxIA 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13796))

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.

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Notes

  1. 1.

    A Boolean fluent can be mapped into a \( \{0,1\} \) numeric fluent.

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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).

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Authors and Affiliations

  1. Università degli Studi di Brescia, Brescia, Italy

    Enrico Scala

  2. University of Huddersfield, Huddersfield, UK

    Thomas L. McCluskey & Mauro Vallati

Authors
  1. Enrico Scala
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  2. Thomas L. McCluskey
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  3. Mauro Vallati
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Correspondence to Mauro Vallati .

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Editors and Affiliations

  1. University of Udine, Udine, Italy

    Agostino Dovier

  2. University of Udine, Udine, Italy

    Angelo Montanari

  3. National Research Council (CNR-ISTC), Rome, Italy

    Andrea Orlandini

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Scala, E., McCluskey, T.L., Vallati, M. (2023). Verification of Numeric Planning Problems Through Domain Dynamic Consistency. In: Dovier, A., Montanari, A., Orlandini, A. (eds) AIxIA 2022 – Advances in Artificial Intelligence. AIxIA 2022. Lecture Notes in Computer Science(), vol 13796. Springer, Cham. https://doi.org/10.1007/978-3-031-27181-6_12

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  • DOI: https://doi.org/10.1007/978-3-031-27181-6_12

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