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Information Flows In Causal Networks

Author

Listed:
  • NIHAT AY

    (Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, D-04103 Leipzig, Germany;
    Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA)

  • DANIEL POLANI

    (Algorithms and Adaptive Systems Research Groups, School of Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK)

Abstract

We use a notion of causal independence based on intervention, which is a fundamental concept of the theory of causal networks, to define a measure for the strength of a causal effect. We call this measure "information flow" and compare it with known information flow measures such as transfer entropy.

Suggested Citation

  • Nihat Ay & Daniel Polani, 2008. "Information Flows In Causal Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 17-41.
    • Handle: RePEc:wsi:acsxxx:v:11:y:2008:i:01:n:s0219525908001465
    DOI: 10.1142/S0219525908001465
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    Cited by:

    1. Temel, Tugrul & Phumpiu, Paul, 2023. "Policy Design from a Network Perspective: Targeting a Sector, Cascade of Links, Network Resilience," MPRA Paper 118466, University Library of Munich, Germany.
    2. Masafumi Oizumi & Larissa Albantakis & Giulio Tononi, 2014. "From the Phenomenology to the Mechanisms of Consciousness: Integrated Information Theory 3.0," PLOS Computational Biology, Public Library of Science, vol. 10(5), pages 1-25, May.
    3. van Elteren, Casper & Quax, Rick & Sloot, Peter, 2022. "Dynamic importance of network nodes is poorly predicted by static structural features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    4. William G P Mayner & William Marshall & Larissa Albantakis & Graham Findlay & Robert Marchman & Giulio Tononi, 2018. "PyPhi: A toolbox for integrated information theory," PLOS Computational Biology, Public Library of Science, vol. 14(7), pages 1-21, July.
    5. Rajan, Rishabh & Rana, Nripendra P. & Parameswar, Nakul & Dhir, Sanjay & Sushil, & Dwivedi, Yogesh K., 2021. "Developing a modified total interpretive structural model (M-TISM) for organizational strategic cybersecurity management," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    6. Shanmugavel, Nagarajan & Balakrishnan, Janarthanan, 2023. "Influence of pro-environmental behaviour towards behavioural intention of electric vehicles," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    7. Temel, Tugrul & Phumpiu, Paul, 2023. "Policy Design from a Network Perspective: Targeting a Sector, Cascade of Links, Network Resilience," MPRA Paper 118389, University Library of Munich, Germany.

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