Objection-based causal networks

Authors:
Adnan Y. Darwiche
Affiliations:
Computer Science Department, Stanford University
Venue:
UAI'92 Proceedings of the Eighth international conference on Uncertainty in artificial intelligence
Year:
1992

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Abstract

This paper introduces the notion of objection-based causal networks, which resemble probabilistic causal networks except that they are quantified using objections. An objection is a logical sentence and denotes a condition under which a causal dependency does not exist. Objection-based causal networks enjoy almost all the properties that make probabilistic causal networks popular, with the added advantage that objections are, arguably, more intuitive than probabilities.