论文标题
混淆幽灵渠道和因果关系：一种新的因果信息流动
Confounding Ghost Channels and Causality: A New Approach to Causal Information Flows
论文作者
论文摘要
信息理论提供了一个基本框架，用于量化通过渠道的信息流，正式马尔可夫内核。但是，诸如相互信息和条件互信息之类的数量不一定反映了这种流量的因果性质。我们认为，这通常是基于与给定通道无关的Sigma代数条件的结果。我们提出了基于基于sigma代数家族的（有条件的）共同信息的版本，该信息与基础通道相结合。这导致过滤，使我们能够证明相应的因果链规则是所提出方法中的基本要求。
Information theory provides a fundamental framework for the quantification of information flows through channels, formally Markov kernels. However, quantities such as mutual information and conditional mutual information do not necessarily reflect the causal nature of such flows. We argue that this is often the result of conditioning based on sigma algebras that are not associated with the given channels. We propose a version of the (conditional) mutual information based on families of sigma algebras that are coupled with the underlying channel. This leads to filtrations which allow us to prove a corresponding causal chain rule as a basic requirement within the presented approach.
