@article {2977907, title = {Causality and explanation in the sciences}, journal = {Theoria - revista de teoria historia y fundamentos de la ciencia}, volume = {27}, number = {2}, year = {2012}, pages = {133{\textendash}136}, abstract = {

Editors{\textquoteright} introduction to the special issue on the Causality and Explanation in the Sciences conference, held at the University of Ghent in September 2011.

}, issn = {0495-4548}, author = {Leuridan, Bert and Weber, Erik} } @article {999416, title = {Can mechanisms really replace laws of nature?}, journal = {Philosophy of Science}, volume = {77}, number = {3}, year = {2010}, pages = {317{\textendash}340}, abstract = {

Today, mechanisms and mechanistic explanation are very popular in philosophy of science and are deemed a welcome alternative to laws of nature and deductive-nomological explanation. Starting from Mitchell{\textquoteright}s pragmatic notion of laws, I cast doubt on their status as a genuine alternative. I argue that (1) all complex-systems mechanisms onto-logically must rely on stable regularities, while (2) the reverse need not hold. Analogously, (3) models of mechanisms must incorporate pragmatic laws, while (4) such laws themselves need not always refer to underlying mechanisms. Finally, I show that Mitchell{\textquoteright}s account is more encompassing than the mechanistic account

}, issn = {0031-8248}, url = {http://dx.doi.org/10.1086/652959}, author = {Leuridan, Bert} } @article {594869, title = {Causal discovery and the problem of ignorance: an adaptive logic approach}, journal = {Journal of Applied Logic}, volume = {7}, number = {2}, year = {2009}, pages = {188{\textendash}205}, abstract = {

In this paper, I want to substantiate three related claims regarding causal discovery from non-experimental data. Firstly, in scientific practice, the problem of ignorance is ubiquitous, persistent, and far-reaching. Intuitively, the problem of ignorance bears upon the following situation. A set of random variables VV is studied but only partly tested for (conditional) independencies; i.e. for some variables A and B it is not known whether they are (conditionally) independent. Secondly, Judea Pearl{\textquoteright}s most meritorious and influential algorithm for causal discovery (the IC algorithm) cannot be applied in cases of ignorance. It presupposes that a full list of (conditional) independence relations is on hand and it would lead to unsatisfactory results when applied to partial lists. Finally, the problem of ignorance is successfully treated by means of ALIC, the adaptive logic for causal discovery presented in this paper.

}, issn = {1570-8683}, doi = {10.1016/j.jal.2007.11.004}, url = {http://dx.doi.org/10.1016/j.jal.2007.11.004}, author = {Leuridan, Bert} }