Duration Consistency Filtering for Qualitative Simulation

  • Authors:

  • Tolga Könik;A. C. Cem Say

  • Affiliations:

  • Artificial Intelligence Lab., University of Michigan, Advanced Tech. Bldg., 1101 Beal Ave., Ann Arbor, MI 48109-2110, USA E-mail: konik@umich.edu;Department of Computer Engineering, Boğaziçi University, Bebek 34342, İstanbul, Turkey E-mail: say@boun.edu.tr

  • Venue:
  • Annals of Mathematics and Artificial Intelligence
  • Year:
  • 2003

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Abstract

We present two new qualitative reasoning formalisms, and use them in the construction of a new type of filtering mechanism for qualitative simulators. Our new sign algebra, SR1*, facilitates reasoning about relationships among the signs of collections of real numbers. The comparison calculus, built on top of SR1*, is a general framework that can be used to qualitatively compare the behaviors of two dynamic systems or two excerpts of the behavior of a single dynamic system at different situations. These tools enable us to improve the predictive performance of qualitative simulation algorithms. We show that qualitative simulators can make better use of their input to deduce significant amounts of qualitative information about the relative lengths of the time intervals in their output behavior predictions. Simple techniques employing concepts like symmetry, periodicity, and comparison of the circumstances during multiple traversals of the same region can be used to build a list of facts representing the deduced information about relative durations. The duration consistency filter eliminates spurious behaviors leading to inconsistent combinations of these facts. Surviving behaviors are annotated with richer qualitative descriptions. Used in conjunction with other spurious behavior elimination methods, this approach would increase the ability of qualitative simulators to handle more complex systems.