Spatial Reasoning in Indeterminate Worlds

A Semantics for Model-Based Spatial Reasoning

Model-based reasoning involves proving the truth of a proposition by computation in the semantic domain. In contrast, rule-based reasoning is proving truth by means of formal manipulation of formulas. A growing body of research in cognitive science suggests that human spatial reasoning is model-based, rather than rule-based. The paper begins with a cognitive perspective of model-based reasoning...

Spatial relations between indeterminate regions

Intuitive Modelling of Place Name Regions for Spatial Information Retrieval

Reasoning about spatial relevance is important for intelligent spatial information retrieval. In heterogeneous and distributed systems like the Semantic Web, spatial reasoning has to be based on light-weight, interoperable and easy-to-use spatial metadata. In this paper we present an approach to an intuitive and user-friendly creation and application of spatial metadata that are used for spatia...

A Mereological Approach to Representing Spatial Vagueness*

Spatial reasoning is crucial in many AI application domains, such as robotics, qualitative and naive physics, and some types of planning . Qualitative reasoning is often required ; and in many of these cases, uncertainty or imprecision about the spatial extent of particular entities has to be represented and coped with . This paper develops an axiomatisation of a relation of `crisping' (reducin...

Topological Reasoning for Identifying a Complete Set of Topological Predicates between Vague Spatial Objects

Current implementations of spatial databases are not capable of handling data that is intrinsically indeterminate or vague. The goal of the Vague Spatial Algebra (VASA) project is to define concepts and implementations that will address this problem. In this paper we further develop work on topological predicates between vague spatial objects. The new developments make use of spatial reasoning ...