Information decomposition of targeteffects from multi-source interactions: perspectives on previous, current and future work

  • The formulation of the Partial Information Decomposition (PID) framework by Williams and Beer in 2010 attracted a significant amount of attention to the problem of defining redundant (or shared), unique and synergistic (or complementary) components of mutual information that a set of source variables provides about a target. This attention resulted in a number of measures proposed to capture these concepts, theoretical investigations into such measures, and applications to empirical data (in particular to datasets from neuroscience). In this Special Issue on “Information Decomposition of Target Effects from Multi-Source Interactions” at Entropy, we have gathered current work on such information decomposition approaches from many of the leading research groups in the field. We begin our editorial by providing the reader with a review of previous information decomposition research, including an overview of the variety of measures proposed, how they have been interpreted and applied to empirical investigations. We then introduce the articles included in the special issue one by one, providing a similar categorisation of these articles into: i. proposals of new measures; ii. theoretical investigations into properties and interpretations of such approaches, and iii. applications of these measures in empirical studies. We finish by providing an outlook on the future of the field.

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Author:Joseph T. Lizier, Nils Bertschinger, Jürgen Jost, Michael WibralORCiDGND
URN:urn:nbn:de:hebis:30:3-514808
DOI:https://doi.org/10.3390/e20040307
ISSN:1099-4300
Parent Title (English):Entropy
Publisher:MDPI
Place of publication:Basel
Document Type:Article
Language:English
Year of Completion:2018
Date of first Publication:2018/04/23
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2019/11/11
Tag:complementary information; information decomposition; mutual information; redundancy; redundant information; synergy; unique information
Volume:20
Issue:4, Art. 307
Page Number:10
First Page:1
Last Page:10
Note:
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
HeBIS-PPN:456370536
Institutes:Informatik und Mathematik / Informatik
Medizin / Medizin
Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
PACS-Classification:00.00.00 GENERAL / 05.00.00 Statistical physics, thermodynamics, and nonlinear dynamical systems (see also 02.50.-r Probability theory, stochastic processes, and statistics) / 05.65.+b Self-organized systems (see also 45.70.-n in classical mechanics of discrete systems)
80.00.00 INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY / 87.00.00 Biological and medical physics / 87.19.-j Properties of higher organisms / 87.19.L- Neuroscience / 87.19.lo Information theory
80.00.00 INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY / 89.00.00 Other areas of applied and interdisciplinary physics / 89.70.-a Information and communication theory (for telecommunications, see 84.40.Ua; for optical communications, see 42.79.Sz; for quantum information, see 03.67.-a; for applications to neuroscience, see 87.19.lo) / 89.70.Cf Entropy and other measures of information
80.00.00 INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY / 89.00.00 Other areas of applied and interdisciplinary physics / 89.75.-k Complex systems / 89.75.Fb Structures and organization in complex systems
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - Namensnennung 4.0