2012
DOI: 10.1016/j.artint.2012.04.001
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Conflict-driven answer set solving: From theory to practice

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Cited by 359 publications
(394 citation statements)
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“…We modified the problem by introducing additional complexities to enrich its structure and create possibilities for non-trivial modeling enhancements requiring a deeper understanding of problem properties. 4 In our experiments we aimed to understand relative advantages of sophisticated search procedures involving conflict-driven clause learning and backjumping of the ASP solver clingo versus the idea of limiting grounding and delegating some constraint solving tasks to a specialized constraint solver employed by clingcon -an idea central to CASP. We experimented with two sets of instances: a small set of 30 instances, where the integer parameters were quite small, and a large set also of 30 instances, where the integer parameters were substantially larger.…”
Section: Introductionmentioning
confidence: 99%
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“…We modified the problem by introducing additional complexities to enrich its structure and create possibilities for non-trivial modeling enhancements requiring a deeper understanding of problem properties. 4 In our experiments we aimed to understand relative advantages of sophisticated search procedures involving conflict-driven clause learning and backjumping of the ASP solver clingo versus the idea of limiting grounding and delegating some constraint solving tasks to a specialized constraint solver employed by clingcon -an idea central to CASP. We experimented with two sets of instances: a small set of 30 instances, where the integer parameters were quite small, and a large set also of 30 instances, where the integer parameters were substantially larger.…”
Section: Introductionmentioning
confidence: 99%
“…For our study we selected the highly optimized ASP system clingo 1 [4] that is based on the ASP grounder gringo [3] and the ASP solver clasp [4], and a CASP system clingcon 2 [5] that is based on modifications of gringo, clasp, and the constraint solver gecode 3 . To conduct the experiments we handcrafted a benchmark called a weighted-sequence problem.…”
Section: Introductionmentioning
confidence: 99%
“…Assume 4 The particular encoding is 1≤i≤n+1 { n j=1 xi,j} ∪ 1≤i<i ≤n+1,1≤j≤n {¬xi,j ∨ ¬x i ,j }. 5 The intuitive idea is that the extension allows for reducing PHP n+1 n to PHP n n−1 with a polynomial number of Resolution steps.…”
Section: Pigeonhole Principle Separates Extended Asp Tableaux From Asmentioning
confidence: 99%
“…Each PHP n+1 n is unsatisfiable since there is no bijective mapping from an (n + 1)-element set to an n-element set. [23] for achieving a polynomial-length E-RES proof of a clausal encoding of the pigeonhole principle 4 , we define the polynomial size program extension…”
Section: Pigeonhole Principle Separates Extended Asp Tableaux From Asmentioning
confidence: 99%
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