Constraint Acquisition with Recommendation Queries

Daoudi, Abderrazak; Mechqrane, Younes; Bessiere, Christian; Lazaar, Nadjib; Bouyakhf, El-Houssine

Constraint Acquisition with Recommendation Queries

Abderrazak Daoudi, Younes Mechqrane, Christian Bessière, Nadjib Lazaar, El-Houssine Bouyakhf

Download BibTeX Cite

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Pages 720-725.

Abstract

Constraint acquisition systems assist the non-expert user in modeling her problem as a constraint network. Most existing constraint acquisition systems interact with the user by asking her to classify an example as positive or negative. Such queries do not use the structure of the problem and can thus lead the user to answer a large number of queries. In this paper, we propose Predict&Ask, an algorithm based on the prediction of missing constraints in the partial network learned so far. Such missing constraints are directly asked to the user through recommendation queries, a new, more informative kind of queries. Predict&Ask can be plugged in any constraint acquisition system. We experimentally compare the QuAcq system to an extended version boosted by the use of our recommendation queries. The results show that the extended version improves the basic QuAcq.

Abderrazak Daoudi, Younes Mechqrane, Christian Bessiere, Nadjib Lazaar, and El-Houssine Bouyakhf. 2016. Constraint Acquisition with Recommendation Queries. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16. IJCAI, 720–725. https://ijcai.org/proceedings/2016/108

@inproceedings{ijcai2016p108,
  title     = {Constraint Acquisition with Recommendation Queries},
  author    = {Daoudi, Abderrazak and Mechqrane, Younes and Bessiere, Christian and Lazaar, Nadjib and Bouyakhf, El-Houssine},
  booktitle = {Proceedings of the Twenty-Fifth International Joint Conference on
               Artificial Intelligence, {IJCAI-16}},
  publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
  editor    = {Subbarao Kambhampati},
  pages     = {720--725},
  year      = {2016},
  month     = {7},
  url       = {https://ijcai.org/proceedings/2016/108},
}

TY  - CPAPER
TI  - Constraint Acquisition with Recommendation Queries
AU  - Daoudi, Abderrazak
AU  - Mechqrane, Younes
AU  - Bessiere, Christian
AU  - Lazaar, Nadjib
AU  - Bouyakhf, El-Houssine
T2  - Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-16
PB  - AAAI Press / International Joint Conferences on Artificial Intelligence
PY  - 2016
SP  - 720
EP  - 725
UR  - https://ijcai.org/proceedings/2016/108
ER  -