Introducing possibilistic logic in ILP for dealing with exceptions

In this paper we propose a new formalization of the inductive logic programming (ILP) problem for a better handling of exceptions. It is now encoded in first-order possibilistic logic. This allows us to handle exceptions by means of prioritized rules, thus taking lessons from non-monotonic reasoning...

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Veröffentlicht in:	Artificial intelligence Jg. 171; H. 16; S. 939 - 950
Hauptverfasser:	Serrurier, Mathieu, Prade, Henri
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.11.2007 Elsevier
Schlagworte:	Applied sciences Artificial intelligence Computer Science Computer science; control theory; systems Exact sciences and technology Inductive logic programming Learning and adaptive systems Machine Learning Non-monotonic reasoning Possibilistic logic Inductive logic programming Possibilistic logic Non-monotonic reasoning Exception handling Priority Algorithmics Competitive algorithms Circumscription Possibility theory First order logic Simulated annealing Artificial intelligence Mathematical programming
ISSN:	0004-3702, 1872-7921
Online-Zugang:	Volltext
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