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Conference Papers Year : 2016

Multiple Constraint Aquisition

Robin Arcangioli
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Nadjib Lazaar

Abstract

QUACQ is a constraint acquisition system that as- sists a non-expert user to model her problem as a constraint network by classifying (partial) exam- ples as positive or negative. For each negative ex- ample, QUACQ focuses onto a constraint of the tar- get network. The drawback is that the user may need to answer a great number of such examples to learn all the constraints. In this paper, we provide a new approach that is able to learn a maximum num- ber of constraints violated by a given negative ex- ample. Finally we give an experimental evaluation that shows that our approach improves on QUACQ.
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Dates and versions

lirmm-01374712 , version 1 (30-09-2016)

Identifiers

  • HAL Id : lirmm-01374712 , version 1

Cite

Robin Arcangioli, Christian Bessiere, Nadjib Lazaar. Multiple Constraint Aquisition. IJCAI: International Joint Conference on Artificial Intelligence, Jul 2016, New York City, United States. pp.698-704. ⟨lirmm-01374712⟩
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