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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
Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables , which is solved by constraint satisfaction methods.
A direct correspondence between the constraint satisfaction problem and the homomorphism problem can be established. For a given constraint satisfaction problem, one can build a pair of relational structures, the first encoding the variables and the signatures of constraints, the second encoding the domains and the relations of the constraints.
In a feedback or parallel constraint satisfaction network, activation passes around symmetrically connected nodes until the activation of all the nodes asymptotes or "relaxes" into a state that satisfies the constraints among the nodes. This process allows for the integration of a number of different sources of information in parallel. [2]
Another method for finding out whether a constraint satisfaction problem has a join tree uses the primal graph of the problem, rather than the dual graph. The primal graph of a constraint satisfaction problem is a graph whose nodes are problem variables and whose edges represent the presence of two variables in the same constraint. A join tree ...
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.
The following are the decomposition methods defined for binary constraint satisfaction problems. Since a problem can be made binary by translating it into its dual problem or using hidden variables, these methods can be indirectly used to provide a tree decomposition for arbitrary constraint satisfaction problems.
In artificial intelligence and operations research, a Weighted Constraint Satisfaction Problem (WCSP), also known as Valued Constraint Satisfaction Problem (VCSP), is a generalization of a constraint satisfaction problem (CSP) where some of the constraints can be violated (according to a violation degree) and in which preferences among solutions can be expressed.