AIMar 27, 2013

Modeling uncertain and vague knowledge in possibility and evidence theories

arXiv:1304.2349v120 citations
Originality Synthesis-oriented
AI Analysis

It addresses the problem of modeling vagueness in AI, but appears incremental as it builds on existing uncertainty theories.

The paper advocates for using possibility and evidence theories to model uncertain and vague knowledge in AI, positioning this as a response to arguments favoring probability.

This paper advocates the usefulness of new theories of uncertainty for the purpose of modeling some facets of uncertain knowledge, especially vagueness, in AI. It can be viewed as a partial reply to Cheeseman's (among others) defense of probability.

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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