By Marie Pelleau

Constraint Programming goals at fixing tough combinatorial difficulties, with a computation time expanding in perform exponentially. The tools are this present day effective adequate to resolve huge business difficulties, in a established framework. even if, solvers are devoted to a unmarried variable sort: integer or actual. fixing combined difficulties depends on advert hoc variations. In one other box, summary Interpretation bargains instruments to turn out software houses, by means of learning an abstraction in their concrete semantics, that's, the set of attainable values of the variables in the course of an execution. a variety of representations for those abstractions were proposed. they're referred to as summary domain names. summary domain names can combine any form of variables, or even signify family members among the variables.

In this paintings, we outline summary domain names for Constraint Programming, so that it will construct a conventional fixing technique, facing either integer and genuine variables. We additionally examine the octagons summary area, already outlined in summary Interpretation. Guiding the quest via the octagonal kin, we receive stable effects on a continual benchmark. We additionally outline our fixing strategy utilizing summary Interpretation recommendations, which will contain current summary domain names. Our solver, AbSolute, is ready to remedy combined difficulties and use relational domains.

  • Exploits the over-approximation ways to combine AI instruments within the equipment of CP
  • Exploits the relationships captured to unravel non-stop difficulties extra effectively
  • Learn from the builders of a solver in a position to dealing with virtually all summary domains

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Abstract Domains in Constraint Programming by Marie Pelleau

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