Qualitative Spatial Representation and Reasoning: A Hierarchical Approach

Qualitative Spatial Representation and Reasoning: A Hierarchical Approach

The ability to reason in space is crucial for agents in order to make informed decisions. Current high-level qualitative approaches to spatial reasoning has serious deficiencies in not reflecting the hierarchical nature of spatial data and human spatial cognition. This paper proposes a framework for hierarchical representation and reasoning about topological information, where a continuous mode...

Qualitative Spatial Representation and Reasoning

The need for spatial representations and spatial reasoning is ubiquitous in AI – from robot planning and navigation, to interpreting visual inputs, to understanding natural language – in all these cases the need to represent and reason about spatial aspects of the world is of key importance. Related fields of research, such as geographic information science (GIScience) [71], have also driven th...

Qualitative Spatial Representation and Reasoning: An Overview

Qualitative Spatial Representation and Reasoning Techniques

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 is an updated version of 25]) I will survey the state of the art in Qualitative Spatial Reasoning, covering representation and r...

SparQ: A Toolbox for Qualitative Spatial Representation and Reasoning

Amultitude of calculi for qualitative spatial reasoning (QSR) has been proposed during the last two decades. The number of practical applications that make use of QSR techniques is, however, comparatively small. One reason for this may be seen in the difficulty for people from outside the field to incorporate the required reasoning techniques into their software. Sometimes, proposed calculi are...