Causal Structure Search: Philosophical Foundations and Future Problems
Richard Scheines and Peter Spirtes, Carnegie Mellon University
We briefly discuss the recent history of causal discovery and the core
philosophical foundations underlying Causal Bayes Nets: the Causal Markov
Axiom and Faithfulness. We then discuss the problems that arise around how
one defines the variables for analysis. We discuss the problem of discretizing
variables, the problem of variables that are logically related, the problem
of automatically finding meaningful and interpretable variables, and a decision
theory problem between defining variables that are uncertain but perhaps
strong causes vs. variables that are more certain but weak causes.