Seeing Things: Inventive Reasoning with Geometric Analogies and Topographic Maps

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 structuremapping theory with an attributematching process. We use structure matching to solve geometric analogy problems that involve manipulating attribute information, such as colors and patterns. Structure matching is also used to creatively interpret topographic (land-cover) maps, adding a wealth of semantic knowledge and providing a far richer interpretation of the raw data. We return to the geometric proportional analogies, identify alternate attribute matching processes that are required to solve different categories of problems. Finally, we assess some implications for computationally creative and inventive models