Publication
Title
Causal discovery and the problem of ignorance : an adaptive logic approach
Author
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.
Language
English
Source (journal)
Journal of applied logic. - Place of publication unknown
Publication
Place of publication unknown : 2009
ISSN
1570-8683
Volume/pages
7:2(2009), p. 188-205
ISI
000270263600005
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Publication type
Subject
External links
Web of Science
Record
Identification
Creation 19.02.2014
Last edited 16.07.2017
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