We identify an important class of symmetries in constraintprogramming, arising from matrices of decision variables where rows and columns can be swapped. Whilst lexicographically ordering the rows(columns) breaks all...
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this paper develops a secure distributed constraint Satisfaction algorithm. A Distributed constraint Satisfaction Problem (DisCSP) is a CSP in which variables and constraints are distributed among multiple agents. A m...
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A difficulty that arises frequently when writing a constraint solver is to determine the constraint propagation and simplification algorithm. In previous work, different methods for automatic generation of propagation...
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One of the key factors in the efficiency of backtracking algorithms is the rule they use to decide on which variable to branch next (namely, the variable ordering heuristics). In this paper, we give a formulation of d...
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In the scope of distributed constraint reasoning, the main algorithms presented so far have a feature in common: the addition of links between previously unrelated agents, before or during search. Our work presents a ...
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In recent years, many constraint-specific filtering algorithms have been introduced. Such algorithms use the semantics of the constraint to perform filtering more efficiently than a generic algorithm. the usefulness o...
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Adding constraints to a basic CSP model can significantly reduce search,e.g. for Golomb rulers [6]. the generation process is usually performed by hand, although some recent work has focused on automatically generatin...
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(纸本)3540428631
Adding constraints to a basic CSP model can significantly reduce search,e.g. for Golomb rulers [6]. the generation process is usually performed by hand, although some recent work has focused on automatically generating symmetry breaking constraints [4]and (less so)on generating implied constraints [5]. We describe an approach to generating implied,symmetry breaking and specialisation constraints and apply this technique to quasigroup construction [10].
In recent years, many works have been carried out to solve over-constrained problems, and more specifically the Maximal constraint Satisfaction Problem (Max-CSP), where the goal is to minimize the number of constraint...
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