Symbolic Boolean manipulation with ordered binary-decision diagrams
ACM Computing Surveys (CSUR)
A Reactive Implementation of Pos Using ROBDDs
PLILP '96 Proceedings of the 8th International Symposium on Programming Languages: Implementations, Logics, and Programs
Cardinal: A Finite Sets Constraint Solver
Constraints
Fast Set Bounds Propagation using BDDs
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Solving set constraint satisfaction problems using ROBDDs
Journal of Artificial Intelligence Research
An attempt to dynamically break symmetries in the social golfers problem
CSCLP'06 Proceedings of the constraint solving and contraint logic programming 11th annual ERCIM international conference on Recent advances in constraints
Fast set bounds propagation using a BDD-SAT hybrid
Journal of Artificial Intelligence Research
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Most propagation-based set constraint solvers approximate the set of possible sets that a variable can take by upper and lower bounds, and perform so-called set bounds propagation However Lagoon and Stuckey have shown that using reduced ordered binary decision diagrams (ROBDDs) one can create a practical set domain propagator that keeps all information (possibly exponential in size) about the set of possible set values for a set variable In this paper we first show that we can use the same ROBDD approach to build an efficient bounds propagator The main advantage of this approach to set bounds propagation is that we need not laboriously determine set bounds propagations rules for each new constraint, they can be computed automatically In addition we can eliminate intermediate variables, and build stronger set bounds propagators than with the usual approach We then show how we can combine this with the set domain propagation approach of Lagoon and Stuckey to create a more efficient set domain propagation solver.