ABSTRACT
Qualitative reasoning is the area of artificial intelligence (AI) that creates representations for continuous aspects of the world, such as space, time, and quantity, which support reasoning with very little information. Typically, it has focused on scientific and engineering domains, hence its other name, qualitative physics. It is motivated by two observations. First, people draw useful and subtle conclusions about the physical world without equations. In our daily lives we figure out what is happening around us and how we can affect it, working with far less data, and less precise data, than would be required to use traditional, purely quantitative methods. Creating software for robots that operate in unconstrained environments and modeling human cognition require understanding how this can be done. Second, scientists and engineers appear to use qualitative reasoning when initially understanding a problem, when setting up more formal methods to solve particular problems, and when interpreting the results of quantitative simulations, calculations, or measurements. Thus, advances in qualitative physics should lead to the creation of more flexible software that can help engineers and scientists.
