Intuitive Direction Concepts

Experiments in this article test the hypothesis that formal direction models used in artificial intelligence correspond to intuitive direction concepts of humans. Cognitively adequate formal models of spatial relations are important for information retrieval tasks, cognitive robotics, and multiple spatial reasoning applications. We detail two experiments using two objects (airplanes) systematically located in relation to each other. Participants performed a grouping task to make their intuitive direction concepts explicit. The results reveal an important, so far insufficiently discussed aspect of cognitive direction concepts: Intuitive (natural) direction concepts do not follow a one-size-fits-all strategy. The behavioral data only forms a clear picture after participants\u27 competing strategies are identified and separated into categories (groups) themselves. The results are important for researchers and designers of spatial formalisms as they demonstrate that modeling cognitive direction concepts formally requires a flexible approach to capture group differences

An inference system for relationships between spatial granularities

Spatial granularities allow one to qualify classical data adding them space locations. In order to compare data qualified with different granularities and to associate data to different granularities (e.g., in analysis similar to drill-down and roll-up operations), it is neces- sary to know how the involved granularities are related. However, the explicit evaluation of these relationships may be heavy from a computational point of view. Moreover, the explicit evaluation of these relationships could not be requested, as relationships can be derived from already established ones. Thus, in this paper, we propose an inference system for deriving spatial relationships that definitely hold, starting from a given set of relationships between spatial granularities, without evaluating them explicitly