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Conference Papers Year : 2021

Parallel Constraint Acquisition

Nadjib Lazaar

Abstract

Constraint acquisition systems assist the non-expert user in modelling her problem as a constraint network. QUACQ is a sequential constraint acquisition algorithm that generates queries as (partial) examples to be classified as positive or negative. The drawbacks are that the user may need to answer a great number of such examples, within a significant waiting time between two examples, to learn all the constraints. In this paper, we propose PACQ, a portfolio-based parallel constraint acquisition system. The design of PACQ benefits from having several users sharing the same target problem. Moreover, each user is involved in a particular acquisition session, opened in parallel to improve the overall performance of the whole system. We prove the correctness of PACQ and we give an experimental evaluation that shows that our approach improves on QUACQ.
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Dates and versions

lirmm-03687351 , version 1 (03-06-2022)

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Nadjib Lazaar. Parallel Constraint Acquisition. AAAI 2021 - 35th Conference on Artificial Intelligence, Sep 2021, virtually, Canada. pp.3860-3867, ⟨10.1609/aaai.v35i5.16504⟩. ⟨lirmm-03687351⟩
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