An operational information decomposition via synergistic disclosure
Publication Date
2020Journal Title
Journal of Physics A: Mathematical and Theoretical
ISSN
1751-8113
Publisher
IOP Publishing
Volume
53
Issue
48
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Rosas, F., Mediano, P., Rassouli, B., & Barrett, A. (2020). An operational information decomposition via synergistic disclosure. Journal of Physics A: Mathematical and Theoretical, 53 (48) https://doi.org/10.1088/1751-8121/abb723
Abstract
<jats:title>Abstract</jats:title>
<jats:p>Multivariate information decompositions hold promise to yield insight into complex systems, and stand out for their ability to identify synergistic phenomena. However, the adoption of these approaches has been hindered by there being multiple possible decompositions, and no precise guidance for preferring one over the others. At the heart of this disagreement lies the absence of a clear operational interpretation of what synergistic information is. Here we fill this gap by proposing a new information decomposition based on a novel operationalisation of informational synergy, which leverages recent developments in the literature of data privacy. Our decomposition is defined for any number of information sources, and its atoms can be calculated using elementary optimisation techniques. The decomposition provides a natural coarse-graining that scales gracefully with the system’s size, and is applicable in a wide range of scenarios of practical interest.</jats:p>
Keywords
complex systems, synergy, information theory, high-order statistics, partial information decomposition
Sponsorship
Wellcome Trust (210920/Z/18/Z)
Identifiers
aabb723, abb723, jphysa-113894.r1
External DOI: https://doi.org/10.1088/1751-8121/abb723
This record's URL: https://www.repository.cam.ac.uk/handle/1810/332050
Rights
Licence:
https://creativecommons.org/licenses/by/4.0/
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