Similarity-based Qualitative Simulation: A preliminary report
نویسنده
چکیده
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 work on a different approach, similarity-based qualitative simulation, which uses standard QR representations but with analogical processing to predict and explain behaviors. We discuss the motivation and progress towards a theory of similarity-based qualitative simulation, illustrated with examples from the first running prototype.
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