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Found 12 papers, 2 papers with code
Towards a Model of Puzznic
We report on progress in modelling and solving Puzznic, a video game requiring the player to plan sequences of moves to clear a grid by matching blocks.
Challenges in Modelling and Solving Plotting with PDDL
We study a planning problem based on Plotting, a tile-matching puzzle video game published by Taito in 1989.
Learning to Select SAT Encodings for Pseudo-Boolean and Linear Integer Constraints
We show that it is possible to select encodings effectively using a standard set of features for constraint problems; however we obtain better performance with a new set of features specifically designed for the pseudo-Boolean and linear constraints.
A Framework for Generating Informative Benchmark Instances
This separation presents an opportunity for automated approaches to generate instance data that define instances that are graded (solvable at a certain difficulty level for a solver) or can discriminate between two solving approaches.
Automatic Tabulation in Constraint Models
The performance of a constraint model can often be improved by converting a subproblem into a single table constraint.
Savile Row Manual
We describe the constraint modelling tool Savile Row, its input language and its main features.
Towards Reformulating Essence Specifications for Robustness
The Essence language allows a user to specify a constraint problem at a level of abstraction above that at which constraint modelling decisions are made.
SAT Encodings for Pseudo-Boolean Constraints Together With At-Most-One Constraints
When solving a combinatorial problem using propositional satisfiability (SAT), the encoding of the problem is of vital importance.
A Review of Literature on Parallel Constraint Solving
As multicore computing is now standard, it seems irresponsible for constraints researchers to ignore the implications of it.
Generalized Support and Formal Development of Constraint Propagators
One key concept in constraint programming is propagation: reasoning on a constraint or set of constraints to derive new facts, typically to remove values from the domains of decision variables.
Short and Long Supports for Constraint Propagation
We also introduce a variant algorithm HaggisGAC-Stable, which is adapted to avoid work on backtracking and in some cases can be faster and have significant reductions in memory use.
