Taming Discretised PDDL+ through Multiple Discretisations

Authors

  • Matteo Cardellini DIBRIS, University of Genova, Genova, Italy
  • Marco Maratea DeMaCS, University of Calabria, Rende, Italy
  • Francesco Percassi School of Computing and Engineering, University of Huddersfield, Huddersfield, UK
  • Enrico Scala Dipartimento di Ingegneria dell’Informazione, Universit`a degli Studi di Brescia, Brescia, Italy
  • Mauro Vallati School of Computing and Engineering, University of Huddersfield, Huddersfield, UK

DOI:

https://doi.org/10.1609/icaps.v34i1.31461

Abstract

The PDDL+ formalism allows the use of planning techniques in applications that require the ability to perform hybrid discrete-continuous reasoning. PDDL+ problems are notoriously challenging to tackle, and to reason upon them a well-established approach is discretisation. Existing systems rely on a single discretisation delta or, at most, two: a simulation delta to model the dynamics of the environment, and a planning delta, that is used to specify when decisions can be taken. However, there exist cases where this rigid schema is not ideal, for instance when agents with very different speeds need to cooperate or interact in a shared environment, and a more flexible approach that can accommodate more deltas is necessary. To address the needs of this class of hybrid planning problems, in this paper we introduce a reformulation approach that allows the encapsulation of different levels of discretisation in PDDL+ models, hence allowing any domain-independent planning engine to reap the benefits. Further, we provide the community with a new set of benchmarks that highlights the limits of fixed discretisation.

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Published

2024-05-30

How to Cite

Cardellini, M., Maratea, M., Percassi, F., Scala, E., & Vallati, M. (2024). Taming Discretised PDDL+ through Multiple Discretisations. Proceedings of the International Conference on Automated Planning and Scheduling, 34(1), 59-67. https://doi.org/10.1609/icaps.v34i1.31461