Self-explanatory simulations: scaling up to large models

Kenneth D Forbus*, Brian Falkenhainer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations


Qualitative reasoners have been hamstrung by the inability to analyze large models. This includes self-explanatory simulators, which tightly integrate qualitative and numerical models to provide both precision and explanatory power. While they have important potential applications in training, instruction, and conceptual design, a critical step towards realizing this potential is the ability to build simulators for medium-sized systems (i.e., on the order of ten to twenty independent parameters). This paper describes a new method for developing self-explanatory simulators which scales up. While our method involves qualitative analysis, it does not rely on envisioning or any other form of qualitative simulation. We describe the results of an implemented system which uses this method, and analyze its limitations and potential.

Original languageEnglish (US)
Title of host publicationProceedings Tenth National Conference on Artificial Intelligence
PublisherPubl by AAAI
Number of pages6
ISBN (Print)0262510634
StatePublished - Dec 1 1992
EventProceedings Tenth National Conference on Artificial Intelligence - AAAI-92 - San Jose, CA, USA
Duration: Jul 12 1992Jul 16 1992


OtherProceedings Tenth National Conference on Artificial Intelligence - AAAI-92
CitySan Jose, CA, USA

ASJC Scopus subject areas

  • Engineering(all)


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