Article
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Preserved in Portico This version is not peer-reviewed
A Measure of Synergy Based on Union Information
Version 1
: Received: 16 January 2024 / Approved: 19 January 2024 / Online: 22 January 2024 (09:29:15 CET)
Version 2 : Received: 24 January 2024 / Approved: 24 January 2024 / Online: 25 January 2024 (09:11:09 CET)
Version 2 : Received: 24 January 2024 / Approved: 24 January 2024 / Online: 25 January 2024 (09:11:09 CET)
A peer-reviewed article of this Preprint also exists.
Gomes, A.F.C.; Figueiredo, M.A.T. A Measure of Synergy Based on Union Information. Entropy 2024, 26, 271. Gomes, A.F.C.; Figueiredo, M.A.T. A Measure of Synergy Based on Union Information. Entropy 2024, 26, 271.
Abstract
The partial information decomposition (PID) framework is concerned with decomposing the information that a set of (two or more) random variables (the sources) has about another variable (the target) into three types of information: unique, redundant, and synergistic. Classical information theory alone does not provide a unique way to decompose information in this manner and additional assumptions have to be made. One often overlooked way to do this decomposition is using a so-called measure of union information – which quantifies the information that is present in at least one of the sources – from which a synergy measure stems. In this paper, we introduce a new measure of union information based on adopting a communication channel perspective, compare it with existing measures, and study some of its properties. We also include a comprehensive critical review of characterizations of union information and synergy measures that have been proposed in the literature.
Keywords
information theory; partial information decomposition; union information; synergy; communication channels.; mutual information
Subject
Computer Science and Mathematics, Probability and Statistics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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