AIMar 6, 2013

Partially Specified Belief Functions

arXiv:1303.1513v17 citations
Originality Synthesis-oriented
AI Analysis

This work addresses a specific issue in belief function theory for researchers in uncertainty reasoning, but it appears incremental as it builds on established principles.

The paper tackles the problem of determining a complete belief function from partial belief values on subsets, using a new focusing principle alongside minimum commitment, and compares the resulting procedure with existing methods like minimum specificity and least commitment.

This paper presents a procedure to determine a complete belief function from the known values of belief for some of the subsets of the frame of discerment. The method is based on the principle of minimum commitment and a new principle called the focusing principle. This additional principle is based on the idea that belief is specified for the most relevant sets: the focal elements. The resulting procedure is compared with existing methods of building complete belief functions: the minimum specificity principle and the least commitment principle.

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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