Home > Reasoning with causality > Reasoning with causality: Sequence index

Reasoning with causality: Sequence index

This sequence explores formalisations of causality. It is split into two parts: The first focuses is a series of reading notes from my reading of the epilogue to  Causality: Models, Reasoning, and Inference by Judea Pearl which deals with reasoning with causal information.

The second focuses specifically on the use of Bayesian Networks in causal reasoning and is based on the paper Causal reasoning with causal models by Kevin Korb, Charles Twardy, Toby Handfield and Graham Oppy.

Section 3 explores a number of relevant concepts based on a variety of papers written by Kevin Korb and various coauthors.

Section 1. Reasoning with causal information

Post 1: Causality and graphical methods

Post 2: A causal calculus: Processing causal information

Post 3: Reasoning with causality: an example

Section 2. Causal reasoning and bayesian networks

Post 4: An introduction to Bayesian networks in causal modeling

Post 5: Is a causal interpretation of Bayes Nets fundamental?

Post 6: Uses of Bayes Nets in causality: Modeling type and token causal relevance

Section 3. Further topics in formalising causality

Post 7: Probabilistic causality

Post 8: Categories and types of intervention

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