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A Sound (But Incomplete) Polynomial Translation from Discretised PDDL+ to Numeric Planning

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AIxIA 2021 – Advances in Artificial Intelligence (AIxIA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13196))

Abstract

pddl+ is an expressive planning formalism that enables the modelling of domains having both discrete and continuous dynamics. Recently, two mappings for translating discretised pddl+ problems into a numeric a-temporal task have been proposed. Such translations produce a task of exponential or polynomial size w.r.t. the size of the native task. In this work, starting from the above-mentioned polynomial translation, we introduce a sound but not generally complete variant that has the potential to improve the performance of numeric planning engines. We define the subclass of problems where the variant is safely applicable, and we assess the advantages of such a translation.

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Notes

  1. 1.

    We use positive and negative literals to short-cut the assignments \( f = \top \) and \( f = \bot \).

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Acknowledgements

Francesco Percassi and Mauro Vallati were supported by a UKRI Future Leaders Fellowship [grant number MR/T041196/1].

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Authors and Affiliations

  1. University of Huddersfield, Huddersfield, UK

    Francesco Percassi & Mauro Vallati

  2. Università degli Studi di Brescia, Brescia, Italy

    Enrico Scala

Authors
  1. Francesco Percassi
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  2. Enrico Scala
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  3. Mauro Vallati
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Corresponding author

Correspondence to Francesco Percassi .

Editor information

Editors and Affiliations

  1. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Stefania Bandini

  2. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Francesca Gasparini

  3. Department of Informatics, Bioengineering, Robotics and Systems Engineering, University of Genoa, Genova, Italy

    Viviana Mascardi

  4. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Matteo Palmonari

  5. Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milan, Italy

    Giuseppe Vizzari

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Percassi, F., Scala, E., Vallati, M. (2022). A Sound (But Incomplete) Polynomial Translation from Discretised PDDL+ to Numeric Planning. In: Bandini, S., Gasparini, F., Mascardi, V., Palmonari, M., Vizzari, G. (eds) AIxIA 2021 – Advances in Artificial Intelligence. AIxIA 2021. Lecture Notes in Computer Science(), vol 13196. Springer, Cham. https://doi.org/10.1007/978-3-031-08421-8_2

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  • DOI: https://doi.org/10.1007/978-3-031-08421-8_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08420-1

  • Online ISBN: 978-3-031-08421-8

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