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International Conference on Principles and Practice of Constraint Programming

CP 2018: Principles and Practice of Constraint Programming pp 30–46Cite as

A Constraint-Based Encoding for Domain-Independent Temporal Planning

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11008))

Abstract

We present a general constraint-based encoding for domain-independent task planning. Task planning is characterized by causal relationships expressed as conditions and effects of optional actions. Possible actions are typically represented by templates, where each template can be instantiated into a number of primitive actions.

While most previous work for domain-independent task planning has focused on primitive actions in a state-oriented view, our encoding uses a fully lifted representation at the level of action templates. It follows a time-oriented view in the spirit of previous work in constraint-based scheduling.

As a result, the proposed encoding is simple and compact as it grows with the number of actions in a solution plan rather than the number of possible primitive actions. When solved with an SMT solver, we show that the proposed encoding is slightly more efficient than state-of-the-art methods on temporally constrained planning benchmarks while clearly outperforming other fully constraint-based approaches.

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Notes

  1. 1.

    Note that this integer based representation of time is no less expressive than a real-valued representation when forbidding instantaneous changes, as common in temporal planning [15].

  2. 2.

    The original chronicle model used transitions instead of effects. We use effects to more closely match the classical definition of planning problems and simplify the presentation. Note that transitions can still be straightforwardly encoded by combining a condition and an effect.

  3. 3.

    Omitted in our translations are the hierarchical and resource constructs of ANML that are beyond the scope of this paper.

  4. 4.

    https://github.com/laas/fape/tree/master/planning/domains.

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Authors and Affiliations

  1. University of Genoa, Genoa, Italy

    Arthur Bit-Monnot

  2. University of Sassari, Sassari, Italy

    Arthur Bit-Monnot

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  1. Arthur Bit-Monnot
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Correspondence to Arthur Bit-Monnot .

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Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    John Hooker

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Bit-Monnot, A. (2018). A Constraint-Based Encoding for Domain-Independent Temporal Planning. In: Hooker, J. (eds) Principles and Practice of Constraint Programming. CP 2018. Lecture Notes in Computer Science(), vol 11008. Springer, Cham. https://doi.org/10.1007/978-3-319-98334-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-98334-9_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98333-2

  • Online ISBN: 978-3-319-98334-9

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