English

The Parameterized Complexity of Global Constraints

Artificial Intelligence 2009-03-04 v1 Computational Complexity

Abstract

We argue that parameterized complexity is a useful tool with which to study global constraints. In particular, we show that many global constraints which are intractable to propagate completely have natural parameters which make them fixed-parameter tractable and which are easy to compute. This tractability tends either to be the result of a simple dynamic program or of a decomposition which has a strong backdoor of bounded size. This strong backdoor is often a cycle cutset. We also show that parameterized complexity can be used to study other aspects of constraint programming like symmetry breaking. For instance, we prove that value symmetry is fixed-parameter tractable to break in the number of symmetries. Finally, we argue that parameterized complexity can be used to derive results about the approximability of constraint propagation.

Keywords

Cite

@article{arxiv.0903.0467,
  title  = {The Parameterized Complexity of Global Constraints},
  author = {Christian Bessiere and Emmanuel Hebrard and Brahim Hnich and Zeynep Kiziltan and Toby Walsh},
  journal= {arXiv preprint arXiv:0903.0467},
  year   = {2009}
}

Comments

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence

R2 v1 2026-06-21T12:17:41.176Z