Combining Qualitative and Quantitative Knowledge to Generate Models of Physical Systems
Abstract
All major approaches to Qualitative Reasoning rely on the existence of a model of the physical system. However, the task of finding a model is usually far from trivial. Within the area of electrical engineering, model building methods have been developed to automatically deduce models from measurements. In this paper we explicitly show how to incorporate qualitative knowledge in order to apply these methods to situations where they do not behave satisfactorily. A program has been developed and applied to a non-trivial example. The qualitative input, in terms of an incomplete bond graph, and the resulting output can be used to form a more complete bond graph. This more informative model is suitable for further reasoning. VI.1 Introduction 1 1 Introduction The major approaches to qualitative reasoning (QR), all rely on the existence of a model of the physical system. All of them have developed model languages, that is, languages for representing qualitative knowledge about physical ...
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Text
Söderman and Strömberg. "Combining Qualitative and Quantitative Knowledge to Generate Models of Physical Systems." International Joint Conference on Artificial Intelligence, 1991.Markdown
[Söderman and Strömberg. "Combining Qualitative and Quantitative Knowledge to Generate Models of Physical Systems." International Joint Conference on Artificial Intelligence, 1991.](https://mlanthology.org/ijcai/1991/soderman1991ijcai-combining/)BibTeX
@inproceedings{soderman1991ijcai-combining,
title = {{Combining Qualitative and Quantitative Knowledge to Generate Models of Physical Systems}},
author = {Söderman, Ulf and Strömberg, Jan-Erik},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {1991},
pages = {1158-1163},
url = {https://mlanthology.org/ijcai/1991/soderman1991ijcai-combining/}
}