Causality Beyond Association or Covariation: Hierarchy, Asymmetry, and Developing over Time
Keywords: Causality, Association, Bayesian Inference
Abstract: The question "Is causality really different from covariation/association?" runs through the whole study about modeling causal inference. Firstly it asks about the organization of causal inference, which is thought to be hierarchical and convariation computation works further in the process in this essay. Secondly it requires representable difference to make theoretical distinction, which can be offered by asymmetry of cause and effect. Only when difference can be perceived can it really make sense. So it finally implicates the question "If the difference really exists, how do we distinguish them in real life?" Several forms of cues such as temporal order, prior knowledge, statistical relations and intervention can be acquired from the world and help us with causal inference.
Submission Number: 67
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