JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 2    Issue : 5    Date : July 2007

Aristotle’s Square Revisited to Frame Discovery Science
Mohammad Afshar, Christopher Dartnell, Dominique Luzeaux, Jean Sallantin, and Yannick Tognetti
Page(s): 54-66
Full Text:
PDF (689 KB)


Abstract
The paper attempts to give a formal framework to capture the entire process of scientific discovery
including hypothesis formation, reasoning, identifying contradictions, peer reviewing, reformulating
and so on. Data mining can be seen as one step in this complex process of interactive learning of
an empirical theory This paper uses the terminology from paraconsistent logic and paracomplete
logic that extends Aristotle square in a hypercube of oppositions which defines or substantiates any
step of the discovery process. The central formal notions are validated on a mathematical scientific
discovery game, and an industrial application in the field of Drug Discovery illustrates how the
presented framework combines different learning processes to predict pharmaco-kinetic properties
(ADME-T) and adverse side effects of therapeutic drug molecules.

Index Terms
Machine Learning, Scientific Method, Logical Reasoning Framework, Aristotle’s Square of
Oppositions