Similarity-based Qualitative Simulation

People are remarkably good at using their common sense to predict and explain behavior. Qualitative modeling has provided formalisms that seem to capture many important aspects of human mental models, but standard qualitative simulation algorithms have properties that make them implausible candidates for modeling the flexibility, robustness, and speed of human reasoning. This paper describes a different approach, similarity-based qualitative simulation, which uses standard QR representations but with analogical processing to predict and explain behaviors. We summarize the problems with existing QR processing models as psychological accounts and outline the theory of similaritybased qualitative simulation. We illustrate the utility of this approach by a number of examples, generated with a prototype implementation.