Integration of qualitative and quantitative methods in visual reasoning

Abstract

Describes how commonsense spatial reasoning is accomplished in a computational model that is primarily qualitative in nature, but which allows the smooth integration of quantitative methods as and when necessary. This model, termed visual reasoning, is characterized by representations that have symbolic and imaginal parts, visual operations that access spatial information contained in the imaginal parts, and visual cases which encode chunks of inferential knowledge. The authors have identified three conditions under which the invocation of quantitative or numerical methods become necessary in order for visual reasoning to proceed. These are described and illustrated by three examples of problem solving that show how quantitative methods get integrated into the framework of visual reasoning. >