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Quantifying synergistic information

Citation

Griffith, Virgil (2014) Quantifying synergistic information. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechTHESIS:12132013-161604752

Abstract

Within the microcosm of information theory, I explore what it means for a system to be functionally irreducible. This is operationalized as quantifying the extent to which cooperative or “synergistic” effects enable random variables X1, ... , Xn to predict (have mutual information about) a single target random variable Y . In Chapter 1, we introduce the problem with some emblematic examples. In Chapter 2, we show how six different measures from the existing literature fail to quantify this notion of synergistic mutual information. In Chapter 3 we take a step towards a measure of synergy which yields the first nontrivial lowerbound on synergistic mutual information. In Chapter 4, we find that synergy is but the weakest notion of a broader concept of irreducibility. In Chapter 5, we apply our results from Chapters 3 and 4 towards grounding Giulio Tononi’s ambitious φ measure which attempts to quantify the magnitude of consciousness experience.

Item Type:Thesis (Dissertation (Ph.D.))
Subject Keywords:information theory, synergy, consciousness, irreducibility
Degree Grantor:California Institute of Technology
Division:Engineering and Applied Science
Major Option:Computation and Neural Systems
Awards:Demetriades-Tsafka-Kokkalis Prize in Entrepreneurship or Related Fields, 2009
Thesis Availability:Public (worldwide access)
Research Advisor(s):
  • Koch, Christof
Thesis Committee:
  • Perona, Pietro (chair)
  • Koch, Christof
  • Ho, Tracey C.
  • Beck, James L.
  • Bruck, Jehoshua
Defense Date:2 December 2013
Non-Caltech Author Email:i (AT) virgil.gr
Additional Information:Those interested in reading my thesis are encouraged to instead read the papers on arxiv.org. They cover the same material in more "bite-size chunks".
Funders:
Funding AgencyGrant Number
DOE CSGF (Department of Energy Computational Science Graduate Fellowship)UNSPECIFIED
Department of Homeland Security Graduate FellowshipUNSPECIFIED
Paul G. Allen Family FoundationUNSPECIFIED
Record Number:CaltechTHESIS:12132013-161604752
Persistent URL:http://resolver.caltech.edu/CaltechTHESIS:12132013-161604752
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/1205.4265arXivQuantifying Synergistic Mutual Information - Adapted for ch. 2 and 3
http://arxiv.org/abs/1311.7442arXivIrreducibility is Minimum Synergy Among Parts - Adapted for ch. 4
http://arxiv.org/abs/1310.1538arXivIntersection Information based on Common Randomness - Adapted for ch. 3
http://arxiv.org/abs/1401.0978arXivA Principled Infotheoretic φ-like Measure - Adapted for ch. 5
Default Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:8041
Collection:CaltechTHESIS
Deposited By: Virgil Griffith
Deposited On:27 Feb 2014 19:55
Last Modified:16 Jun 2014 21:28

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