Automatic abduction of qualitative models

Authors:
Bradley L. Richards;Ina Kraan;Benjamin J. Kuipers
Affiliations:
Dept. of Computer Sciences, University of Texas, Austin, Texas;Dept. of Artificial Intelligence, University of Edinburgh, Edinburgh, Scotland, UK;Dept. of Computer Sciences, University of Texas, Austin, Austin, Texas
Venue:
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Year:
1992

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Abstract

We describe a method of automatically abducing qualitative models from descriptions of behaviors. We generate, from either quantitative or qualitative data, models in the form of qualitative differential equations suitable for use by QSIM. Constraints are generated and filtered both by comparison with the input behaviors and by dimensional analysis. If the user provides complete information on the input behaviors and the dimensions of the input variables, the resulting model is unique, maximally constrained, and guaranteed to reproduce the input behaviors. If the user provides incomplete information, our method will still generate a model which reproduces the input behaviors, but the model may no longer be unique. Incompleteness can take several forms: missing dimensions, values of variables, or entire variables.