Credibility discounting in the theory of approximate reasoning

We are concerned with the problem of introducing credibility type information into reasoning systems. The concept of credibility allows us to discount information provided by agents. An important characteristic of this kind of procedure is that a complete lack of credibility rather than resulting in the negation of the information provided results in the nullification of the information provided. We suggest a representational scheme for credibility qualification in the theory of approximate reasoning. We discuss the concept of relative credibility. By this idea we mean to indicate situations in which the credibility of a piece of evidence is determined by its compatibility with higher priority evidence. This situation leads to structures very much in the spirit of nonmonotonic reasoning.

[1]  Ronald R. Yager,et al.  A note on weighted queries in information retrieval systems , 1987, J. Am. Soc. Inf. Sci..

[2]  Lotfi A. Zadeh,et al.  A Theory of Approximate Reasoning , 1979 .

[3]  Ronald R. Yager,et al.  On considerations of credibility of evidence , 1992, Int. J. Approx. Reason..

[4]  Ronald R. Yager.  A note on weighted queries in information retrieval systems , 1987, J. Am. Soc. Inf. Sci..

[5]  R R Yager,et al.  Using Approximate Reasoning to Represent Default Knowledge , 1987, Artif. Intell..

[6]  Didier Dubois,et al.  A review of fuzzy set aggregation connectives , 1985, Inf. Sci..

[7]  Philippe Smets.  Non-standard logics for automated reasoning , 1988 .

[8]  Petr Hájek,et al.  On Belief Functions , 1992, Advanced Topics in Artificial Intelligence.

[9]  Matthew L. Ginsberg,et al.  Readings in Nonmonotonic Reasoning , 1987, AAAI 1987.

[10]  Ronald R. Yager,et al.  Multiple objective decision-making using fuzzy sets , 1977 .

[11]  Lotfi A. Zadeh,et al.  Fuzzy sets and information granularity , 1996 .

[12]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[13]  Henri Prade,et al.  A Computational Approach to Approximate and Plausible Reasoning with Applications to Expert Systems , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.