Information flows in causal networks
Information flows in causal networks
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DOI：
10.1142/s0219525908001465
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发表时间：
2008-02-01
影响因子：
0.4
通讯作者：
Polani, Daniel
中科院分区：
文献类型：
--
作者：
Ay, Nihat;Polani, Daniel
我们使用基于干预的因果独立性概念，这是因果网络理论的基本概念，来定义因果效应强度的度量。我们称之为“信息流”，并将其与已知的信息流度量（如传递熵）进行比较。
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.