Vol. 15 No. 4, © The Author, 2005. Published by Oxford University Press. All rights reserved.
Original Articles |
Probabilistic Logic and Induction
Institute of Discrete Mathematics and Geometry, Technical University of Vienna, Wiedner Hauptstrasse 810/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.