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- W1527777107 abstract "Since the early 1970s, researchers in artificial intelligence (AI) have investigated a class of combinatorial problems that became known as constraint-satisfaction problems (CSP). The input to such a problem consists of a set of variables, a set of possible values for the variables, and a set of constraints between the variables; the question is to determine whether there is an assignment of values to the variables that satisfies the given constraints. The study of constraint satisfaction occupies a prominent place in artificial intelligence, because many problems that arise in different areas can be modelled as constraint-satisfaction problems in a natural way; these areas include Boolean satisfiability, temporal reasoning, belief maintenance, machine vision, and scheduling (cf. [Dec92a,Kum92,Mes89, Tsa93]). In its full generality, constraint satisfaction is an NP-complete problem. For this reason, researchers in artificial intelligence have pursued both heuristics for constraint-satisfaction problems and tractable cases obtained by imposing various restrictions on the input (cf. [MF93,Dec92a,DM94,Fro97,PJ97])." @default.
- W1527777107 created "2016-06-24" @default.
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- W1527777107 date "2008-01-01" @default.
- W1527777107 modified "2023-10-16" @default.
- W1527777107 title "A Logical Approach to Constraint Satisfaction" @default.
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- W1527777107 doi "https://doi.org/10.1007/978-3-540-92800-3_6" @default.
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