Information flows in causal networks

N. Ay; D. Polani

doi:10.1142/S0219525908001465

Information flows in causal networks

N. Ay
, D. Polani

Research output: Contribution to journal › Article › peer-review

229 Citations (Scopus)

494 Downloads (Pure)

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

Original language	English
Pages (from-to)	17-41
Journal	Advances in Complex Systems
Volume	11
Issue number	1
DOIs	https://doi.org/10.1142/S0219525908001465
Publication status	Published - 2008

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Information flows in causal networks

Abstract

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