AINov 30, 2019

Belief and plausibility measures for D numbers

arXiv:1912.00109v1
Originality Synthesis-oriented
AI Analysis

This work addresses foundational issues in uncertainty modeling for researchers in information fusion and decision-making, but it appears incremental as it builds directly on existing D number theory.

The paper tackled the problem of undefined basic concepts in D number theory, a generalization of Dempster-Shafer theory for handling uncertain information with non-exclusiveness and incompleteness, by proposing belief and plausibility measures for D numbers and revealing their basic properties.

As a generalization of Dempster-Shafer theory, D number theory provides a framework to deal with uncertain information with non-exclusiveness and incompleteness. However, some basic concepts in D number theory are not well defined. In this note, the belief and plausibility measures for D numbers have been proposed, and basic properties of these measures have been revealed as well.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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