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