Title
Causal discovery and the problem of ignorance : an adaptive logic approachCausal discovery and the problem of ignorance : an adaptive logic approach
Author
Faculty/Department
Faculty of Arts. Philosophy
Publication type
article
Publication
,
Subject
Mathematics
Engineering sciences. Technology
Computer. Automation
Source (journal)
Journal of applied logic. -
Volume/pages
7(2009):2, p. 188-205
ISSN
1570-8683
ISI
000270263600005
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
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 V 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'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. (C) 2007 Elsevier B.V. All rights reserved.
E-info
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