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Journal of Logic and Computation 2005 15(4):507-515; doi:10.1093/logcom/exi032
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Vol. 15 No. 4, © The Author, 2005. Published by Oxford University Press. All rights reserved.

Original Articles

Probabilistic Logic and Induction

Sebastiaan A. Terwijn

Institute of Discrete Mathematics and Geometry, Technical University of Vienna, Wiedner Hauptstrasse 8–10/E104, A-1040 Vienna, Austria. Email: terwijn{at}logic.at

We give a probabilistic interpretation of first-order formulas based on Valiants model of pac-learning. We study the resulting notion of probabilistic or approximate truth and take some first steps in developing its model theory. In particular we show that every fixed error parameter determining the precision of universal quantification gives rise to a different class of tautologies. Finally we study the inductive inference of first-order formulas from atomic truths.

Keywords: Probabilistic logic, pac-learning


Received 1 April 2005.


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