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Position Papers of the 17th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 31

The Compositional Rule of Inference vs the Bandler-Kohout Subproduct: a Comparison of Two Standard Rules of Inference

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DOI: http://dx.doi.org/10.15439/2022F222

Citation: Position Papers of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 31, pages 19–26 ()

Full text

Abstract. This contribution focuses on the most popular scheme of reasoning in approximate reasoning, generalized modus ponens. Also, we consider the case when the reasoning is performed with one fuzzy rule. Usually, the compositional rule of inference introduced by Zadeh is involved. However, it is also common to use the Bandler-Kohout subproduct. We compare these two rules showing by experimental results the conditions when applying one of them is more appropriate. We concentrate on an example of image transformation where applying a different rule of inference gives a different conclusion. Moreover, we point out some theoretical justifications for particular fuzzy connectives used in both methods (fuzzy implication functions, triangular norms and, in general, fuzzy conjunctions).

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