Waldemar W. Koczkodaj

Prof. Dr. Waldemar W. Koczkodaj


Research Focus & Metrics

Academic Career Length

38Years (1989-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 October 1993 in Mathematical and Computer Modelling
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Journal Article
Closed access
WKWaldemar W. Koczkodaj
Waldemar W. Koczkodaj

1 January 2014 in Fundamenta Informaticae
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Journal Article
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WKWaldemar W. Koczkodaj
Waldemar W. Koczkodaj
RSRyszard Szwarc
Ryszard Szwarc
This study examines the notion of inconsistency in pairwise comparisons for providing an axiomatization for it. It also proposes two inconsistency indicators for pairwise comparisons. The primary motivation for the inconsistency reduction is expressed by a computer industry concept “garbage in, garbage out”. The quality of the output depends on the quality of the input.

1 January 1996 in Information Processing Letters
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Journal Article
Closed access
MHMichael W. Herman
Michael W. Herman
WKWaldemar W. Koczkodaj
Waldemar W. Koczkodaj

1 December 1994 in Information Processing Letters
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Journal Article
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ZDZbigniew Duszak
Zbigniew Duszak
WKWaldemar W. Koczkodaj
Waldemar W. Koczkodaj

16 January 2010 in Logic Journal of the IGPL
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Journal Article
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WKWaldemar W. Koczkodaj
Waldemar W. Koczkodaj
SSS. J. Szarek
S. J. Szarek
A complete proof of convergence of a certain class of reduction algorithms for distance-based inconsistency (defined in 1993) for pairwise comparisons is presented in this paper. Using pairwise comparisons is a powerful method for synthesizing measurements and subjective assessments. From the mathematical point of view, the pairwise comparisons method generates a matrix (say A) of ratio values (aij) of the ith entity compared with the jth entity according to a given criterion. Entities/criteria can be both quantitative or qualitative allowing this method to deal with complex decisions. However, subjective assessments often involve inconsistency, which is usually undesirable. The assessment can be refined via analysis of inconsistency, leading to reduction of the latter. The proposed method of localizing the inconsistency may conceivably be of relevance for nonclassical logics (e.g., paraconsistent logic) and for uncertainty reasoning since it accommodates inconsistency by treating inconsistent data as still useful information.

1 March 2018 in International Journal of Approximate Reasoning
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Journal Article
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WKWaldemar W. Koczkodaj
Waldemar W. Koczkodaj
RUR. Urban
R. Urban