Qualitative and Quantitative Simulation: Bridging the Gap

Shortcomings of qualitative simulation and of quantitative simulation motivate combining them to do simulations exhibiting strengths of both. The resulting class of techniques is called semi-quantitative simulation. One approach to semi-quantitative simulation is to use numeric intervals to represent incomplete quantitative information. In this research we demonstrate semiquantitative simulation using intervals in an implemented semi-quantitative simulator called Q3. Q3 progressively re nes a qualitative simulation, providing increasingly speci c quantitative predictions which can converge to a numerical simulation in the limit while retaining important correctness guarantees from qualitative and interval simulation techniques. Q3's simulations are based on a technique we call step size re nement. While a pure qualitative simulation has a very coarse step size, representing the state of a system trajectory at relatively few qualitatively distinct states, Q3 interpolates newly explicit states between distinct qualitative states, thereby representing more states which instantiate new constraints, leading to improved quantitative inferences. Q3's techniques have been used for prediction, measurement interpretation, diagnosis, and even analysis of the probabilities of qualitative behaviors. Because Q3 shares important expressive and inferential properties of both qualitative and quantitative simulation, Q3 helps to bridge the gap between qualitative and quantitative simulation. This research was supported in part by NSF grants IRI-8905494 and IRI-8904454 and NASA grant NAG 5207, and performed in part for the Jet Propulsion Laboratory, California Institute of Technology, sponsored by the National Aeronautics and Space Administration. Reference herein to any speci c commercial product, process, or service does not constitute or imply its endorsement by any organization.