Abstract
An engineer’s model of a physical system balances accuracy and parsimony: it is as simple as possible while still accounting for the dynamical behavior of the target system. PRET is a computer program that automatically builds such models. Its inputs are a set of observations of some subset of the outputs of a nonlinear system, and its output is an ordinary differential equation that models the internal dynamics of that system. Modeling problems like this have immense and complicated search spaces, and searching them is an imposing technical challenge. PRET exploits a spectrum of AI and engineering techniques to navigate efficiently through these spaces, using a special first-order logic system to decide which technique to use when and how to interpret the results. Its representations and reasoning tactics are designed both to support this flexibility and to leverage any domain knowledge that is available from the practicing engineers who are its target audience. This flexibility and power has let PRET construct accurate, minimal models of a wide variety of applications, ranging from textbook examples to real-world engineering problems.
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Stolle, R., Easley, M., Bradley, E. (2002). Reasoning about Models of Nonlinear Systems. In: Magnani, L., Nersessian, N.J., Pizzi, C. (eds) Logical and Computational Aspects of Model-Based Reasoning. Applied Logic Series, vol 25. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0550-0_12
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DOI: https://doi.org/10.1007/978-94-010-0550-0_12
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