Information Flows in Causal Networks

Nihat Ay and Daniel Polani

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Submission date: 02. May. 2006
published in: Advances in complex systems, 11 (2008) 1, p. 17-41 
DOI number (of the published article): 10.1142/S0219525908001465
Bibtex
MSC-Numbers: 94A15, 94A40, 94B15
Keywords and phrases: information flow, causality, directed acyclic graphs, mutual information

Abstract:
We introduce a notion of causal independence based on virtual 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.