Qualitative spatial representations (original) (raw)

Qualitative Spatial Representation and Reasoning: An Overview

Fundamenta Informaticae, 2001

The eld of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which i s a n updated version of 25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and reasoning issues as well as pointing to some application areas. CON, INCON and WCON CON and INCON, not WCON CON, not INCON or WCON

Qualitative Spatial Representation and Reasoning Techniques

German Conference on Artificial Intelligence, 1997

The field of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which is an updated version of [25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and reasoning issues as well as pointing to some application areas.

Qualitative Spatial Reasoning for Applications

Concepts, Methodologies, Tools, and Applications, 2013

About two decades ago the field of qualitative spatial and temporal reasoning (QSTR) has emerged as a new area of AI research that set out to grasp human-level understanding and reasoning about spatial and temporal entities, linking formal approaches to cognitive theories. Empowering artificial agents with QSTR capabilities is claimed to facilitate manifold applications, including robot navigation, geographic information systems (GIS), natural language understanding and computer-aided design. QSTR is an active field of research that has developed many representation and reasoning approaches so far, but only comparatively few applications exist that actually build on these QSTR techniques.

Qualitative Spatial Representation and Reasoning with the Region Connection Calculus

Geoinformatica, 1997

The eld of Qualitative Spatial Reasoning is now an active research area in its own right within AI (and also in Geographical Information Systems) having grown out of earlier work in philosophical logic and more general Qualitative Reasoning in AI. In this paper (which i s a n updated version of 25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and reasoning issues as well as pointing to some application areas.

SparQ: A toolbox for qualitative spatial representation and reasoning

2006

The term qualitative constraint calculus comprises logical formalisms and algorithmic methods used in the domain of Qualitative Representation and Reasoning, a steadily growing and vital sub-domain of current AI research. In the past 25 years, since P. J. Hayes' work "Naive physics 1: ontology for liquids" (1978) and J. Allen's work "Maintaining knowledge about temporal intervals" (1983), researchers have intensely studied representations of real-world phenomena by describing features of the world in purely qualitative terms. This is because these formalisms aim at describing the commonsense background knowledge on which our human perspective on the physical reality is based. In fact, although qualitative calculi employ concepts from a wide range of mathematical theories (geometrical notions such as lines, half-planes, and angels, topological terms such as interior, boundary, or connectedness, concepts of size and shape, etc.), qualitative representation formalisms usually are built on vocabularies that are close to expressions in natural languages. This entails that qualitative representation formalisms abstract from metrical aspects of the physical reality and, moreover, from (maybe "over"-) sophisticated concept formations used in mathematics or physics.

Representing and Reasoning with Qualitative Spatial Relations About Regions

Spatial and Temporal Reasoning, 1997

This chapter surveys the work of the qualitative spatial reasoning group at the University of Leeds. The group has developed a number of logical calculi for representing and reasoning with qualitative spatial relations over regions. We motivate the use of regions as the primary spatial entity and show how a rich language can be built up from surprisingly few primitives. This language can distinguish between convex and a variety of concave shapes and there is also an extension which handles regions with uncertain boundaries. We also present a variety of reasoning techniques, both for static and dynamic situations. A number of possible application areas are brie y mentioned.