---
title: "Generalized Physical Networks for Automated Model Building"
authors:
  - "Matthew Easley"
  - "Elizabeth Bradley"
doi: ""
url: "https://ijcai.org/proceedings/1999/149"
pdf: "https://ijcai.org/proceedings/1999/0149.pdf"
venue: "Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence"
year: 1999
pages: "1047-1052"
track: "Qualitative Reasoning and Diagnosis"
keywords:
---

# Generalized Physical Networks for Automated Model Building

Matthew Easley, Elizabeth Bradley

*Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence*, pages 1047-1052.

## Abstract

We pr ese nt a new knowledge representation and reasoning framework for mod eling nonlinear dynamical systems. The goa ls of this framework are to smoothly incorporate varying levels of domain knowledge and to tailor the reasoning methods - and hence th e search space - accordingly. Our solution exploits generalized physical networks (GPN), a meta-level representation of idealized two-terminal elements, tog et her with a hierarchy of qualitative and quantitative analysis tools, to produce a dynamic modeling domain whose complexity naturally adapts to the amount of available information about the target system.