Information Flows in Causal Networks
University of Hertfordshire
Max-Planck Institute for Mathematics in the Sciences Leipzig/Santa Fe Institute (External Faculty)
Last modified: August 20, 2007
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.