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'''Constraint programming''' is a [[programming paradigm]] in which a set of [[constraint]]s that a solution must meet are specified rather than set of steps to obtain such a solution.
#REDIRECT [[Logical programming]]▼
Constraint programming is related to [[Logical programming]] and, since both [[Turing-complete]], any logic program can be translated into an equivalent constraint program and ''viceversa''. This is sometimes useful in practice, since a constraint solving program may find an answer faster than a logic derivation program, and it might be desirable to perform this [[translation]] before executing a logic program.
The difference between the two is largely in their styles and approaches to modeling the world. Some problems are more natural (and thus, simpler) to write as logic programs, while some are more natural to write as constraint programs.
The constraint programming approach is to search for a state of the world in which a large number of constraints are satisfied at the same time. A problem is typically stated as a state of the world containing a number of unknown variables. The constraint program searches for values for all the variables.
Temporal concurrent constraint programming (TCC) and non-deterministic temporal concurrent constraint programming (NTCC) are variants of constraint programming that can deal with time.
Some popular application domains for constraint programming are:
*[[Boolean algebra|boolean ___domain]]s, where only true/false constraints apply
*[[Linear algebra|linear ___domain]]s, where only [[linear]] functions are described and analyzed (although approaches to [[non-linear]] problems do exist)
*[[Finite|finite ___domain]]s, where constraints are defined over [[countable set]]s
*Mixed domains, involving two or more of the above
==See also==
*[[Programming paradigm]]
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