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Constraint logic programming is a form of constraint programming, in which logic programming is extended to include concepts from constraint satisfaction. A constraint logic program is a logic program that contains constraints in the body of clauses. An example of a clause including a constraint is A (X, Y):-X + Y > 0, B (X), C (Y).
The reason of over-constraint is the unique geometry of linkages in these mechanisms, which the mobility formula does not take into account. This unique geometry gives rise to "redundant constraints", i.e. when multiple joints are constraining the same degrees of freedom. These redundant constraints are the reason of the over-constraint.
Constraint propagation in constraint satisfaction problems is a typical example of a refinement model, and formula evaluation in spreadsheets are a typical example of a perturbation model. The refinement model is more general, as it does not restrict variables to have a single value, it can lead to several solutions to the same problem.
The bucket elimination algorithm can be adapted for constraint optimization. A given variable can be indeed removed from the problem by replacing all soft constraints containing it with a new soft constraint. The cost of this new constraint is computed assuming a maximal value for every value of the removed variable.
In mathematics, a constraint is a condition of an optimization problem that the solution must satisfy. There are several types of constraints—primarily equality constraints, inequality constraints, and integer constraints. The set of candidate solutions that satisfy all constraints is called the feasible set. [1]
Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...
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