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Learning qualitative physics reasoning from regime analysis

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Artificial Intelligence and Symbolic Mathematical Computing (AISMC 1992)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 737))

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Abstract

One of the very basic rules we learn in an introductory course of physics is that two physical quantities, say Q 1 and Q 2, can only be compared when they have the same dimensional representation and, in addition, should be in the same system of units. This rule is also frequently applied to discard non-matching physcial formulae. In other words, the dimensional consistence of physical formulae must be fulfilled.

The rule we are talking about is in fact known as the Principle of Dimensional Homogeneity (PDH), which states that any physical law has to be dimensionally consistent to be meaningful.

In this paper we show that using the PDH and results from the Regime Analysis, it is possible to reason qualitatively about a physical system. In addition, as the whole process is algorithmic, this allows automating the reasoning through a symbolic computer system. The system QDR-Qualitative Dimensional Reasoner has been developed for this task.

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Authors and Affiliations

  1. Departamento de Ciência da Computação, Universidade Federal de Santa Catarina, 88040.970, Florianópolis, SC, Brazil

    Waldir L. Roque

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  1. Waldir L. Roque
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Jacques Calmet John A. Campbell

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© 1993 Springer-Verlag Berlin Heidelberg

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Roque, W.L. (1993). Learning qualitative physics reasoning from regime analysis. In: Calmet, J., Campbell, J.A. (eds) Artificial Intelligence and Symbolic Mathematical Computing. AISMC 1992. Lecture Notes in Computer Science, vol 737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57322-4_20

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  • DOI: https://doi.org/10.1007/3-540-57322-4_20

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57322-7

  • Online ISBN: 978-3-540-48063-1

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