Case Adaptation with Qualitative Algebras
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 3002-3005.
Abstract
This paper proposes an approach for the adaptation of spatial or temporal cases in a case-based reasoning system. Qualitative algebras are used as spatial and temporal knowledge representation languages. The intuition behind this adaptation approach is to apply a substitution and then repair potential inconsistencies, thanks to belief revision on qualitative algebras. A temporal example from the cooking domain is given.
Valmi Dufour-Lussier, Florence Le Ber, Jean Lieber, and Laura Martin. 2013. Case Adaptation with Qualitative Algebras. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13. IJCAI, 3002–3005. https://ijcai.org/proceedings/2013/445
Dufour-Lussier, V., Le Ber, F., Lieber, J., & Martin, L. (2013). Case Adaptation with Qualitative Algebras. In Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 (pp. 3002–3005). IJCAI. https://ijcai.org/proceedings/2013/445
@inproceedings{ijcai2013p445,
title = {Case Adaptation with Qualitative Algebras},
author = {Dufour-Lussier, Valmi and Le Ber, Florence and Lieber, Jean and Martin, Laura},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {3002--3005},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/445},
}
TY - CPAPER TI - Case Adaptation with Qualitative Algebras AU - Dufour-Lussier, Valmi AU - Le Ber, Florence AU - Lieber, Jean AU - Martin, Laura T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 3002 EP - 3005 UR - https://ijcai.org/proceedings/2013/445 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
