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Non-monotonic characterization of induction and its application to inductive learning

Author
Nuñez, G.; Cortes, U.; Larrosa, J.
Type of activity
Journal article
Journal
International journal of intelligent systems
Date of publication
1995-10
Volume
10
Number
10
First page
895
Last page
927
DOI
https://doi.org/10.1002/int.4550101004 Open in new window
Abstract
In this article a new approach to the formalization of inductive inference in terms of non-monotonic inference is proposed. Induction is characterized as closed-world reasoning from the available data, followed by an inductive jump, which consists in assuming that valid conclusions in the database (assuming closed-world) hold also in the rest of the world. This conception of induction results is adequate to characterize those inference processes that could be formalized, that is, those based in ...
Group of research
IDEAI-UPC - Intelligent Data Science and Artificial Intelligence Research Center
KEMLG - Knowledge Engineering and Machine Learning Group
LOGPROG - Logic and Programming

Participants