Qualitative Spatial Reasoning

Abstract

Artificial Intelligence (AI) has, as one of its central topics, the ability to represent and reason with common sense knowledge. Early forays into common sense reasoning about the physical world involved solving textbook problems on physics and mathematics. These were not adequate for reasoning about most commonplace physical scenarios. A system suggested by DeKleer, involving both quantitative knowledge and qualitative information concerning the physical situation marked the starting point for qualitative physics (Weld & DeKleer, 1990). Hayes’ Naive Physics Manifesto (Hayes, 1985) paved the way for establishing qualitative physics (meantime re-christened qualitative reasoning) as an important topic of research within AI. Qualitative Reasoning (QR) is an approach for dealing with common sense knowledge without recourse to complete quantitative knowledge. Representation of knowledge is through a limited repository of qualitative abstractions. Space and spatial change is an important part of common sense reasoning. Naive Physics Manifesto proposed to represent space-time with four-dimensional histories. Despite early forays such as the Naive Physics Manifesto, representation of space within QR has been ill addressed. Nevertheless, there has been an increasing interest over the last few years in qualitative spatial reasoning - reasoning about space using qualitative abstractions.