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Title: Inhibited effects in CP-logic
Authors: Meert, Wannes
Vennekens, Joost
Issue Date: 17-Sep-2014
Publisher: Springer
Host Document: Lecture Notes in Computer Science vol:8754 pages:350-356
Conference: Probabilistic Graphical Models edition:7 location:Utrecht date:17-19 September 2014
Abstract: An important goal of statistical relational learning formalisms is to develop representations that are compact and expressive but also easy to read and maintain. This is can be achieved by exploiting the modularity of rule-based structures and is related to the noisy-or structure where parents independently influence a joint effect. Typically, these rules are combined in an additive manner where a new rule increases the probability of the effect. In this paper, we present a new language feature for CP-logic, where we allow negation in the head of rules to express the inhibition of an effect in a modular manner. This is a generalization of the inhibited noisy-or structure that can deal with cycles and, foremost, is non-conflicting. We introduce syntax and semantics for this feature and show how this is a natural counterpart to the standard noisy-or. Experimentally, we illustrate that in practice there is no additional cost when performing inference compared to a noisy-or structure.
ISSN: 0302-9743
Publication status: published
KU Leuven publication type: IC
Appears in Collections:Informatics Section
Computer Science Technology TC, Technology Campus De Nayer Sint-Katelijne-Waver
Technologiecluster Computerwetenschappen

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