Self-Explanatory Simulations: An Integration of Qualitative and Quantitative Knowledge

Kenneth D. Forbus, Brian Falkenhainer

A central goal of qualitative physics is to provide a framework for organizing and using quantitative knowledge. One important use of quantitative knowledge is numerical simulation. While current numerical simulators are powerful, they are often hard to construct, do not reveal the assumptions underlying their construction, and do not produce explanations of the behaviors they predict. This paper shows how to combine qualitative and quantitative models to produce a new class of self-explanatory simulations which combine the advantages of both kinds of reasoning. Self-explanatory simulations provide the accuracy of numerical models and the interpretive power of qualitative reasoning. We define what self-explanatory simulations are and show how to construct them automatically. We illustrate their power with some examples generated with an implemented system, SIMGEN. We analyze the limitations of our techniques, and discuss plans for future work.


This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.