Automated modeling of physical systems in the presence of incomplete knowledge
Adam Farquhar · 1993
This dissertation presents an approach to automated reasoning about physical systems in the presence of incomplete knowledge which supports formal analysis, proof of guarantees, has been fully implemented, and applied to substantial domain modeling problems. Predicting and reasoning about the behavior of physical systems is a difficult and important task that is essential to everyday commonsense reasoning and to complex engineering tasks such as design, monitoring, control, or diagnosis. A capability for automated modeling and simulation requires ffl expressiveness to represent incomplete knowledge, ffl algorithms to draw useful inferences about non-trivial systems, and ffl precise semantics to support meaningful guarantees of correctness. In order to clarify the structure of the knowledge required for reasoning about the behavior of physical systems, we distinguish between the model building task which builds a model to describe the system, and the simulation task which uses the mo...