Improved Measures of Integrated Information
Name
Tegmark-2016-Improved Measures of Integrated I.pdf
Size
3.53 MB
Format
Adobe PDF
Checksum (MD5)
6517021f9d3d0d94e4dd5e1841be444b
Author(s)
Tegmark, Max Erik
Date Issued
November 2016
Journal
PLOS Computational Biology
Publisher
Public Library of Science
Citation
Tegmark, Max. “Improved Measures of Integrated Information.” Ed. Anil Seth. PLOS Computational Biology 12.11 (2016): e1005123.
Version
Final published version
Abstract
Although there is growing interest in measuring integrated information in computational and cognitive systems, current methods for doing so in practice are computationally unfeasible. Existing and novel integration measures are investigated and classified by various desirable properties. A simple taxonomy of Φ-measures is presented where they are each characterized by their choice of factorization method (5 options), choice of probability distributions to compare (3 × 4 options) and choice of measure for comparing probability distributions (7 options). When requiring the Φ-measures to satisfy a minimum of attractive properties, these hundreds of options reduce to a mere handful, some of which turn out to be identical. Useful exact and approximate formulas are derived that can be applied to real-world data from laboratory experiments without posing unreasonable computational demands.
MIT Department
Massachusetts Institute of Technology. Department of Physics
MIT Kavli Institute for Astrophysics and Space Research
Terms of Use
Creative Commons Attribution 4.0 International License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1371/journal.pcbi.1005123
