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Optimal Planning with Expressive Action Languages as Constraint Optimization

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Logics in Artificial Intelligence (JELIA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14281))

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Abstract

We consider the problem of optimal planning in deterministic domains specified with expressive action languages. We show how it is possible to reduce such problem to finding an optimal solution of a constraint optimization problem incorporating a bound n on the maximum length of the plan. By solving the latter, we can conclude whether (i) the plan found is optimal even for bounds greater than n; or (ii) we need to increase n; or (iii) it is useless to increase n since the planning problem has no solution.

The authors wish to thank Erika Ábrahám, Francesco Leofante and Marco Maratea for useful discussions about the research topic presented in this paper.

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Notes

  1. 1.

    Formal statement and proof omitted for lack of space.

  2. 2.

    We omit the proof of proposition 1 as it is an easy consequence of the hypothesis and the definitions.

  3. 3.

    The proof is an easy induction on the length of the plan.

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Authors and Affiliations

  1. DIBRIS - University of Genoa, V.le Causa 13, 16145, Genoa, Italy

    Enrico Giunchiglia & Armando Tacchella

Authors
  1. Enrico Giunchiglia
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  2. Armando Tacchella
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Correspondence to Armando Tacchella .

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Editors and Affiliations

  1. TU Dresden, Dresden, Germany

    Sarah Gaggl

  2. Artificial Intelligence Research Institute - IIIA CSIC, Barcelona, Spain

    Maria Vanina Martinez

  3. Umeå University, Umeå, Sweden

    Magdalena Ortiz

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Giunchiglia, E., Tacchella, A. (2023). Optimal Planning with Expressive Action Languages as Constraint Optimization. In: Gaggl, S., Martinez, M.V., Ortiz, M. (eds) Logics in Artificial Intelligence. JELIA 2023. Lecture Notes in Computer Science(), vol 14281. Springer, Cham. https://doi.org/10.1007/978-3-031-43619-2_42

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  • DOI: https://doi.org/10.1007/978-3-031-43619-2_42

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-43619-2

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