Improved Measures of Integrated Information
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 ta...
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| Format: | Article |
| Language: | en_US |
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Public Library of Science
2017
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| Online Access: | http://hdl.handle.net/1721.1/107390 https://orcid.org/0000-0001-7670-7190 |
| _version_ | 1811093984436551680 |
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| author | Tegmark, Max Erik |
| author2 | Massachusetts Institute of Technology. Department of Physics |
| author_facet | Massachusetts Institute of Technology. Department of Physics Tegmark, Max Erik |
| author_sort | Tegmark, Max Erik |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T15:53:46Z |
| format | Article |
| id | mit-1721.1/107390 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T15:53:46Z |
| publishDate | 2017 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/1073902022-09-29T16:54:52Z Improved Measures of Integrated Information Tegmark, Max Erik Massachusetts Institute of Technology. Department of Physics MIT Kavli Institute for Astrophysics and Space Research Tegmark, Max Erik 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. United States. Army Research Office (Grant W911NF-15-1-0300) 2017-03-10T19:24:29Z 2017-03-10T19:24:29Z 2016-11 2016-01 Article http://purl.org/eprint/type/JournalArticle 1553-7358 1553-734X http://hdl.handle.net/1721.1/107390 Tegmark, Max. “Improved Measures of Integrated Information.” Ed. Anil Seth. PLOS Computational Biology 12.11 (2016): e1005123. https://orcid.org/0000-0001-7670-7190 en_US http://dx.doi.org/10.1371/journal.pcbi.1005123 PLOS Computational Biology Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/ application/pdf Public Library of Science PLoS |
| spellingShingle | Tegmark, Max Erik Improved Measures of Integrated Information |
| title | Improved Measures of Integrated Information |
| title_full | Improved Measures of Integrated Information |
| title_fullStr | Improved Measures of Integrated Information |
| title_full_unstemmed | Improved Measures of Integrated Information |
| title_short | Improved Measures of Integrated Information |
| title_sort | improved measures of integrated information |
| url | http://hdl.handle.net/1721.1/107390 https://orcid.org/0000-0001-7670-7190 |
| work_keys_str_mv | AT tegmarkmaxerik improvedmeasuresofintegratedinformation |