JACIII Vol.24 No.1 pp. 83-94
doi: 10.20965/jaciii.2020.p0083


Aggregation of Epistemic Uncertainty in Forms of Possibility and Certainty Factors

Koichi Yamada

Nagaoka University of Technology
1603-1 Kami-Tomioka, Nagaoka, Niigata 940-2188, Japan

April 24, 2019
October 8, 2019
January 20, 2020
uncertainty combination, information aggregation, possibility theory, certainty factors, information source model

Uncertainty aggregation is an important reasoning for making decisions in the real world, which is full of uncertainty. The paper proposes an information source model for aggregating epistemic uncertainties about truth and discusses uncertainty aggregation in the form of possibility distributions. A new combination rule of possibilities for truth is proposed. Then, this paper proceeds to discussion about a traditional but seemingly forgotten representation of uncertainty (i.e., certainty factors (CFs)) and proposes a new interpretation based on possibility theory. CFs have been criticized because of their lack of sound mathematical interpretation from the viewpoint of probability. Thus, this paper first establishes a theory for a sound interpretation using possibility theory. Then it examines aggregation of CFs based on the interpretation and some combination rules of possibility distributions. The paper proposes several combination rules for CFs having sound theoretical basis, one of which is exactly the same as the oft-criticized combination.

Cite this article as:
K. Yamada, “Aggregation of Epistemic Uncertainty in Forms of Possibility and Certainty Factors,” J. Adv. Comput. Intell. Intell. Inform., Vol.24, No.1, pp. 83-94, 2020.
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Last updated on Feb. 26, 2020