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arXiv · 1310.1538

Intersection Information based on Common Randomness

Virgil Griffith·Edwin K. P. Chong·Ryan G. James·Christopher J. Ellison·James P. Crutchfield
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Abstract

The introduction of the partial information decomposition generated a flurry of proposals for defining an intersection information that quantifies how much of "the same information" two or more random variables specify about a target random variable. As of yet, none is wholly satisfactory. A palatable measure of intersection information would provide a principled way to quantify slippery concepts, such as synergy. Here, we introduce an intersection information measure based on the Gács-Körner common random variable that is the first to satisfy the coveted target monotonicity property. Our measure is imperfect, too, and we suggest directions for improvement.

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Virgil Griffith, Edwin K. P. Chong, Ryan G. James, Christopher J. Ellison, James P. Crutchfield. 2015-06-10. Intersection Information based on Common Randomness. https://doi.org/10.3390/e16041985

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