We examine different formalisms for modeling qualitatively physical systems and their associated inferential processes that allow us to derive qualitative predictions from the models. We highlight the mathematical aspects of these processes along with their potential and limitations. The article then bridges to quantitative modeling, highlighting the benefits of qualitative reasoning-based approaches in the framework of system identification, and discusses open research issues.

Mathematical foundations of qualitative reasoning

L Ironi;
2003

Abstract

We examine different formalisms for modeling qualitatively physical systems and their associated inferential processes that allow us to derive qualitative predictions from the models. We highlight the mathematical aspects of these processes along with their potential and limitations. The article then bridges to quantitative modeling, highlighting the benefits of qualitative reasoning-based approaches in the framework of system identification, and discusses open research issues.
2003
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
dynamic systems
simulation
model
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/51480
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