Abstract
One crucial problem in Artificial Intelligence is succeeding in managing uncertain knowledge. By the present paper, a particular type of uncertainty is considered: that on the possible causes of observed effects. Said uncertainty will be formalized by means of the credibility of the causes themselves. Credibility that will be achieved by convolving, through an abductive paradigm: the evidence with which each cause is indicated by obtained observations; the plausibility of the same cause; and the clarity of the performed indication. The issue results as an outline of the matter developed in earlier papers; in it, intermediate passages and proofs are abridged.
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© 1987 Springer-Verlag Berlin Heidelberg
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Arigoni, A.O. (1987). Credibility of abducible multiple causes of observed effects. In: Bouchon, B., Yager, R.R. (eds) Uncertainty in Knowledge-Based Systems. IPMU 1986. Lecture Notes in Computer Science, vol 286. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-18579-8_23
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DOI: https://doi.org/10.1007/3-540-18579-8_23
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