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 International Conference on Complex Systems (ICCS2007)

Information Flows in Causal Networks

Daniel Polani
University of Hertfordshire

Nihat Ay
Max-Planck Institute for Mathematics in the Sciences Leipzig/Santa Fe Institute (External Faculty)

     Full text: Not available
     Last modified: August 20, 2007

Abstract
We introduce a notion of causal independence based on intervention
which is a fundamental concept of the theory of causal networks.
Causal independence allows for defining a measure for the strength
of a causal effect. We call this information flow and compare it
with known information flow measures such as the transfer entropy.







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