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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