On the Modelling of Constraints with Tractable Logical Operators
Abstract
Solving a Constraint Satisfaction Problem (CSP) usually requires a model typically using existing basic constraints. The most flexible form of constraint, ad-hoc (generic) constraints defined with certain constraint representations, such as binary constraint tree (BCT) and decision diagrams, have been proposed where basic constraints in intensional form are insufficient. A modeller may wish to combine basic constraints using logic operators (and, or, negation). However, negation, a key logical operator for expressivity is not tractable in many existing constraint representations. This creates a dilemma, for modelling, we would desire more flexibility, but a model whose operations are intractable may in turn be impractical. In this paper, we give a framework which allows for a tractable negation operator on constraint representations. We apply the framework on the BCT and ordered decision diagram constraints, giving new subforms. These subforms can be strictly more succinct than ordered multi-valued decision diagrams (OMDD), while being as tractable as OMDD for logical combinations. We give applications to show effective propagators from logical combinations and in building large constraint models for configuration problems.
Cite
Text
Wang and Yap. "On the Modelling of Constraints with Tractable Logical Operators." AAAI Conference on Artificial Intelligence, 2025. doi:10.1609/AAAI.V39I11.33238Markdown
[Wang and Yap. "On the Modelling of Constraints with Tractable Logical Operators." AAAI Conference on Artificial Intelligence, 2025.](https://mlanthology.org/aaai/2025/wang2025aaai-modelling/) doi:10.1609/AAAI.V39I11.33238BibTeX
@inproceedings{wang2025aaai-modelling,
title = {{On the Modelling of Constraints with Tractable Logical Operators}},
author = {Wang, Ruiwei and Yap, Roland H. C.},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2025},
pages = {11381-11389},
doi = {10.1609/AAAI.V39I11.33238},
url = {https://mlanthology.org/aaai/2025/wang2025aaai-modelling/}
}