Propagating Regular Counting Constraints


  • Nicolas Beldiceanu Mines de Nantes
  • Pierre Flener Uppsala University
  • Justin Pearson Uppsala University
  • Pascal Van Hentenryck NICTA and Australian National University



Constraints over finite sequences of variables are ubiquitous in sequencing and timetabling. This led to general modelling techniques and generic propagators, often based on deterministic finite automata (DFA) and their extensions. We consider counter-DFAs (cDFA), which provide concise models for regular counting constraints, that is constraints over the number of times a regular-language pattern occurs in a sequence. We show how to enforce domain consistency in polynomial time for at-most and at-least regular counting constraints based on the frequent case of a cDFA with only accepting states and a single counter that can be increased by transitions. We also show that the satisfaction of exact regular counting constraints is NP-hard and that an incomplete propagator for exact regular counting constraints is faster and provides more pruning than the existing propagator from (Beldiceanu, Carlsson, and Petit 2004). Finally, by avoiding the unrolling of the cDFA used by COSTREGULAR, the space complexity reduces from O(n · |Σ| · |Q|) to O(n · (|Σ| + |Q|)), where Σ is the alphabet and Q the state set of the cDFA.




How to Cite

Beldiceanu, N., Flener, P., Pearson, J., & Van Hentenryck, P. (2014). Propagating Regular Counting Constraints. Proceedings of the AAAI Conference on Artificial Intelligence, 28(1).



Main Track: Search and Constraint Satisfaction