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A Numerical Optimisation Based Characterisation of Spatial Reasoning

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Rule Technologies. Research, Tools, and Applications (RuleML 2016)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 9718))

Abstract

We present a novel numerical optimisation based characterisation of spatial reasoning in the context of constraint logic programming (CLP). The approach —formalised and implemented within CLP— is developed as an extension to CLP(QS), a declarative spatial reasoning framework providing a range of mixed quantitative-qualitative spatial representation and reasoning capabilities. We demonstrate the manner in which the numerical optimisation based extensions further enhance the declarative spatial reasoning capabilities of CLP(QS).

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Notes

  1. 1.

    We employ the egg-yolk method of modelling regions with indeterminante boundaries [6] to characterise a class of regions (including polygons) that satisfies topological and relative orientation relations [17]. Each egg-yolk region is an equivalence class for all regions that are contained within the upper approximation (the egg white), and completely contain the lower approximations (the egg yolk).

  2. 2.

    \({\text {CLP}}(\mathcal {QS})\) is implemented in SWI-Prolog, and we have integrated the geometric constraint solver FreeCAD www.freecadweb.org.

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Author information

Authors and Affiliations

  1. University of Münster, Münster, Germany

    Carl Schultz

  2. University of Bremen, Bremen, Germany

    Mehul Bhatt

  3. The DesignSpace Group, Bremen, Germany

    Carl Schultz & Mehul Bhatt

Authors
  1. Carl Schultz
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  2. Mehul Bhatt
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Corresponding author

Correspondence to Carl Schultz .

Editor information

Editors and Affiliations

  1. Universidade Nova de Lisboa, Lisboa, Portugal

    Jose Julio Alferes

  2. Carleton University, Ottawa, Ontario, Canada

    Leopoldo Bertossi

  3. NICTA Queensland, Brisbane, Queensland, Australia

    Guido Governatori

  4. Stony Brook University, Stony Brook, New York, USA

    Paul Fodor

  5. SINTEF/University of Oslo, Oslo, Norway

    Dumitru Roman

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Schultz, C., Bhatt, M. (2016). A Numerical Optimisation Based Characterisation of Spatial Reasoning. In: Alferes, J., Bertossi, L., Governatori, G., Fodor, P., Roman, D. (eds) Rule Technologies. Research, Tools, and Applications. RuleML 2016. Lecture Notes in Computer Science(), vol 9718. Springer, Cham. https://doi.org/10.1007/978-3-319-42019-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-42019-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42018-9

  • Online ISBN: 978-3-319-42019-6

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