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  2. Constraint satisfaction problem - Wikipedia

    en.wikipedia.org/.../Constraint_satisfaction_problem

    The classic model of Constraint Satisfaction Problem defines a model of static, inflexible constraints. This rigid model is a shortcoming that makes it difficult to represent problems easily. [ 33 ] Several modifications of the basic CSP definition have been proposed to adapt the model to a wide variety of problems.

  3. Constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Constraint_satisfaction

    Constraint satisfaction toolkits are software libraries for imperative programming languages that are used to encode and solve a constraint satisfaction problem. Cassowary constraint solver, an open source project for constraint satisfaction (accessible from C, Java, Python and other languages). Comet, a commercial programming language and toolkit

  4. Min-conflicts algorithm - Wikipedia

    en.wikipedia.org/wiki/Min-conflicts_algorithm

    algorithm MIN-CONFLICTS is input: console.csp, A constraint satisfaction problem. max_steps, The number of steps allowed before giving up. current_state, An initial assignment of values for the variables in the csp. output: A solution set of values for the variable or failure.

  5. Complexity of constraint satisfaction - Wikipedia

    en.wikipedia.org/wiki/Complexity_of_constraint...

    Solving a constraint satisfaction problem on a finite domain is an NP-complete problem in general. Research has shown a number of polynomial-time subcases, mostly obtained by restricting either the allowed domains or constraints or the way constraints can be placed over the variables.

  6. Interchangeability algorithm - Wikipedia

    en.wikipedia.org/wiki/Interchangeability_algorithm

    In computer science, an interchangeability algorithm is a technique used to more efficiently solve constraint satisfaction problems (CSP). A CSP is a mathematical problem in which objects, represented by variables, are subject to constraints on the values of those variables; the goal in a CSP is to assign values to the variables that are consistent with the constraints.

  7. Constraint programming - Wikipedia

    en.wikipedia.org/wiki/Constraint_programming

    Constraint propagation works by reducing domains of variables, strengthening constraints, or creating new ones. This leads to a reduction of the search space, making the problem easier to solve by some algorithms. Constraint propagation can also be used as an unsatisfiability checker, incomplete in general but complete in some particular cases.

  8. AC-3 algorithm - Wikipedia

    en.wikipedia.org/wiki/AC-3_algorithm

    Together with the constraints C1 = "X must be even" and C2 = "X + Y must equal 4" we have a CSP that AC-3 can solve. Notice that the actual constraint graph representing this problem must contain two edges between X and Y since C2 is undirected but the graph representation being used by AC-3 is directed. AC-3 solves the problem by first ...

  9. Local search (constraint satisfaction) - Wikipedia

    en.wikipedia.org/wiki/Local_search_(constraint...

    In constraint satisfaction, local search is an incomplete method for finding a solution to a problem. It is based on iteratively improving an assignment of the variables until all constraints are satisfied. In particular, local search algorithms typically modify the value of a variable in an assignment at each step.