First-order qualitative spatial representation languages with convexity

First-order qualitative spatial representation languages with convexity In recent years, there has been considerable interest within the AI community in qualitative descriptions of space. The idea is that a language in which we can say such things as “region a is convex” or “region b is a part of region c” might be sufficient for characterizing useful properties of everyday spatial arrangements, while avoiding complex and error-sensitive numerical coordinate descriptions. However, such qualitative representation languages are inevitably balanced on a semantic knife-edge: too little expressiveness, and they are useless for the everyday tasks we want them for; too much, and they exhibit the over-precision which motivated qualitative representation languages in the first place. The aim of this paper is to demonstrate how sharp that knife-edge is, and thus to establish some limits on what such qualitative spatial description languages might be like. Spatial Cognition and Computation Springer Journals

First-order qualitative spatial representation languages with convexity

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Kluwer Academic Publishers
Copyright © 1999 by Kluwer Academic Publishers
Psychology; Cognitive Psychology
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