Automatic Generation and Selection of Streamlined Constraint Models via Monte Carlo Search on a Model Lattice

  • Patrick Spracklen
  • Özgür AkgünEmail author
  • Ian Miguel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11008)


Streamlined constraint reasoning is the addition of uninferred constraints to a constraint model to reduce the search space, while retaining at least one solution. Previously it has been established that it is possible to generate streamliners automatically from abstract constraint specifications in Essence and that effective combinations of streamliners can allow instances of much larger scale to be solved. A shortcoming of the previous approach was the crude exploration of the power set of all combinations using depth and breadth first search. We present a new approach based on Monte Carlo search over the lattice of streamlined models, which efficiently identifies effective streamliner combinations.



This work was supported via EPSRC EP/P015638/1. We thank our anonymous reviewers for helpful comments.


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Authors and Affiliations

  1. 1.School of Computer ScienceUniversity of St AndrewsSt AndrewsUK

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