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Most combinatoric problems can be modelled naturally by using some kind of logic formulas. We call logic formulas constraints. Two forms of constraints can be be distguished: basic constraints are so simple that they can be solved deterministically, whereas complex constraints cannot. Typical examples for basic constraints are symbolic equations as used in first-order unification. A good examples for complex constraints are arithmetic equations.
In what concernes concurrent constraint programming, basic constraints are accumulated incrementally in a constraint store whereas complex constraints are turned into propagators. Propagators are agents that observe the constraint store. A propagator infers consequences of the constraints in the store and the formula by which it is defined. Such consequence are new constraints which can be either basic or complex again.
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