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This chapter presents a general introduction to causal reasoning based on graphical causal models. First we introduce causal predictions using causal Bayesian networks, including the front door and back door criteria, and the DO calculus, for dealing with cofactors. Then we describe how to solve counterfactuals based on structural causal models.

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Causal Reasoning

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  • 发表日期：

    2026年

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  • Luis Enrique Sucar

摘要

This chapter presents a general introduction to causal reasoning based on graphical causal models. First we introduce causal predictions using causal Bayesian networks, including the front door and back door criteria, and the DO calculus, for dealing with cofactors. Then we describe how to solve counterfactuals based on structural causal models.