@inproceedings{0629ca9e99894195966548acdde5e1d1,
title = "Robust constraint acquisition by sequential analysis",
abstract = "Modeling a combinatorial problem is a hard and error-prone task requiring expertise. Constraint acquisition methods can automate this process by learning constraints from examples of solutions and (usually) non-solutions. We describe a new statistical approach based on sequential analysis that is orders of magnitude faster than existing methods, and gives accurate results on popular benchmarks. It is also robust in the sense that it can learn constraints correctly even when the data contain many errors.",
author = "Steven Prestwich",
note = "Publisher Copyright: {\textcopyright} 2020 The authors and IOS Press.; 24th European Conference on Artificial Intelligence, ECAI 2020, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 ; Conference date: 29-08-2020 Through 08-09-2020",
year = "2020",
month = aug,
day = "24",
doi = "10.3233/FAIA200113",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "355--362",
editor = "\{De Giacomo\}, Giuseppe and Alejandro Catala and Bistra Dilkina and Michela Milano and Senen Barro and Alberto Bugarin and Jerome Lang",
booktitle = "ECAI 2020 - 24th European Conference on Artificial Intelligence, including 10th Conference on Prestigious Applications of Artificial Intelligence, PAIS 2020 - Proceedings",
address = "Netherlands",
}