A computational model is a mathematical representation of a system or process that uses algorithms and simulations to analyze and predict behavior. It integrates computational techniques to solve complex problems, enabling researchers to explore theoretical scenarios and validate hypotheses through numerical experimentation.
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A computational model is a mathematical representation of a system or process that uses algorithms and simulations to analyze and predict behavior. It integrates computational techniques to solve complex problems, enabling researchers to explore theoretical scenarios and validate hypotheses through numerical experimentation.
We describe an instance-based reasoning solution to a variety of spatial reasoning problems. The solution centers on identifying an isomorphic mapping between labelled graphs that represent some problem data and a known solution instance.... more
We describe an instance-based reasoning solution to a variety of spatial reasoning problems. The solution centers on identifying an isomorphic mapping between labelled graphs that represent some problem data and a known solution instance. We describe a number of spatial reasoning problems that are solved by generating non-deductive inferences, integrating topology with area (and other) features. We report the accuracy of our algorithm on different categories of spatial reasoning tasks from the domain of Geographical Information Science. The generality of our approach is illustrated by also solving geometric proportional (IQ-test type) analogy problems.
This paper examines two seemingly unrelated qualitative spatial reasoning domains; geometric proportional analogies and topographic (landcover) maps. We present a Structure Matching algorithm that combines Gentner's structure mapping... more
This paper examines two seemingly unrelated qualitative spatial reasoning domains; geometric proportional analogies and topographic (landcover) maps. We present a Structure Matching algorithm that combines Gentner's structure mapping theory with an attribute matching process. We use structure matching to solve geometric analogy problems that are centered on manipulating attribute information, such as colors and patterns. Structure matching is also used to creatively interpret topographic (land-cover) maps, serving to add a wealth of semantic knowledge and providing a far richer interpretation of the raw data. We return to the geometric proportional analogy problems and identify alternate attribute matching processes that are required to solve different categories of geometric proportional analogy problems. Finally, we assess some implications for computationally creative and inventive models.
This paper examines two seemingly unrelated qualitative spatial reasoning domains; geometric proportional analogies and topographic (land-cover) maps. We present a Structure Matching algorithm that combines Gentner's structure mapping... more
This paper examines two seemingly unrelated qualitative spatial reasoning domains; geometric proportional analogies and topographic (land-cover) maps. We present a Structure Matching algorithm that combines Gentner's structure mapping theory with an attribute matching process.