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  1. SAT-based causal discovery under weaker assumptions. Zhalama, Jiji Zhang, Frederick Eberhardt & Wolfgang Mayer - 2017 - In Zhalama, Jiji Zhang, Frederick Eberhardt & Wolfgang Mayer (eds.), Proceedings of the 33rd Conference on Uncertainty in Artificial Intelligence (UAI). Association for Uncertainty in Artificial Intelligence (AUAI).
    Using the flexibility of recently developed methods for causal discovery based on Boolean satisfiability solvers, we encode a variety of assumptions that weaken the Faithfulness assumption. The encoding results in a number of SAT-based algorithms whose asymptotic correctness relies on weaker conditions than are standardly assumed. This implementation of a whole set of assumptions in the same platform enables us to systematically explore the effect of weakening the Faithfulness assumption on causal discovery. An important effect, suggested by simulation results, is (...)
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  • The PC Algorithm and the Inference to Constitution.Lorenzo Casini & Michael Baumgartner - 2023 - British Journal for the Philosophy of Science 74 (2):405-429.
    Gebharter has proposed using one of the best known Bayesian network causal discovery algorithms, PC, to identify the constitutive dependencies underwriting mechanistic explanations. His proposal assumes that mechanistic constitution behaves like deterministic direct causation, such that PC is directly applicable to mixed variable sets featuring both causal and constitutive dependencies. Gebharter claims that such mixed sets, under certain restrictions, comply with PC’s background assumptions. The aim of this article is to show that Gebharter’s proposal incurs severe problems, ultimately rooted in (...)
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