AIMar 20, 2013

A Modification to Evidential Probability

arXiv:1303.5732v17 citations
Originality Synthesis-oriented
AI Analysis

This work addresses a specific issue in evidential probability theory, offering an incremental improvement for researchers in formal epistemology and statistical reasoning.

The paper tackles the problem of selecting reference classes and intervals in Kyburg's Evidential Probability system when faced with conflicting candidates and no subset dominance, proposing a modification that leads to stronger statistical assertions while largely preserving intuitive appeal.

Selecting the right reference class and the right interval when faced with conflicting candidates and no possibility of establishing subset style dominance has been a problem for Kyburg's Evidential Probability system. Various methods have been proposed by Loui and Kyburg to solve this problem in a way that is both intuitively appealing and justifiable within Kyburg's framework. The scheme proposed in this paper leads to stronger statistical assertions without sacrificing too much of the intuitive appeal of Kyburg's latest proposal.

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