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A Structure-Sensitive Translation from Hybrid to Numeric Planning

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AIxIA 2023 – Advances in Artificial Intelligence (AIxIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14318))

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Abstract

pddl+ is an expressive planning formalism that enables the modelling of hybrid domains with both discrete and continuous dynamics. However, its expressiveness makes this language notoriously difficult to handle natively. To address this challenge, translations from time-discrete pddl+ into numeric pddl2.1 have been proposed as a way to reframe the rich expressiveness of pddl+ into a simpler and more manageable formalism. In this work, we first analyse existing translations and provide a means to compare them in terms of induced state space and the size of the reformulated tasks. Secondly, we propose a novel translation leveraging the structure of the problem to generate a compact reformulation. Our experimental results indicate that the novel translation outperforms the existing ones on a range of benchmarks.

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Notes

  1. 1.

    \(\dot{x} = y\) denotes that the first derivative of x is y.

  2. 2.

    Conditional effects are an important feature in planning formalisms in which the effects of an action are state-dependent [2, 12].

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Acknowledgements

Francesco Percassi and Mauro Vallati were 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.

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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 authors

Correspondence to Francesco Percassi , Enrico Scala or Mauro Vallati .

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Editors and Affiliations

  1. University of Rome Tor Vergata, Rome, Italy

    Roberto Basili

  2. Sapienza University of Rome, Rome, Italy

    Domenico Lembo

  3. Roma Tre University, Rome, Italy

    Carla Limongelli

  4. National Research Council, Rome, Italy

    Andrea Orlandini

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Percassi, F., Scala, E., Vallati, M. (2023). A Structure-Sensitive Translation from Hybrid to Numeric Planning. In: Basili, R., Lembo, D., Limongelli, C., Orlandini, A. (eds) AIxIA 2023 – Advances in Artificial Intelligence. AIxIA 2023. Lecture Notes in Computer Science(), vol 14318. Springer, Cham. https://doi.org/10.1007/978-3-031-47546-7_8

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  • DOI: https://doi.org/10.1007/978-3-031-47546-7_8

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