INFORMATION FLOWS IN CAUSAL NETWORKS-Reference-Cited by-同舟云学术

INFORMATION FLOWS IN CAUSAL NETWORKS

Published:2008-02 Issue:01 Volume:11 Page:17-41
ISSN:0219-5259
Container-title:Advances in Complex Systems
language:en
Short-container-title:Advs. Complex Syst.

Author:

AY NIHAT¹²,POLANI DANIEL³

Affiliation:

1. Max Planck Institute for Mathematics in the Sciences, Inselstrasse 22, D-04103 Leipzig, Germany

2. Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, USA

3. 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.

Publisher

World Scientific Pub Co Pte Lt

Subject

Control and Systems Engineering

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0219525908001465

Reference24 articles.

1. Could information theory provide an ecological theory of sensory processing?

2. Dynamical properties of strongly interacting Markov chains

3. Information Theory and the Brain

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