Quantifying synergistic mutual information
Information Theory
2014-04-02 v6 math.IT
Quantitative Methods
Abstract
Quantifying cooperation or synergy among random variables in predicting a single target random variable is an important problem in many complex systems. We review three prior information-theoretic measures of synergy and introduce a novel synergy measure defined as the difference between the whole and the union of its parts. We apply all four measures against a suite of binary circuits to demonstrate that our measure alone quantifies the intuitive concept of synergy across all examples. We show that for our measure of synergy that independent predictors can have positive redundant information.
Cite
@article{arxiv.1205.4265,
title = {Quantifying synergistic mutual information},
author = {Virgil Griffith and Christof Koch},
journal= {arXiv preprint arXiv:1205.4265},
year = {2014}
}
Comments
15 pages; 12 page appendix. Lots of figures. Guided Self Organization: Inception. Ed: Mikhail Prokopenko. (2014); ISBN 978-3-642-53734-9