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The existence of a solution to a CSP can be viewed as a decision problem. This can be decided by finding a solution, or failing to find a solution after exhaustive search (stochastic algorithms typically never reach an exhaustive conclusion, while directed searches often do, on sufficiently small problems). In some cases the CSP might be known ...
Common spatial pattern (CSP) is a mathematical procedure used in signal processing for separating a multivariate signal into additive subcomponents which have maximum differences in variance between two windows.
The earlier AC algorithms are often considered too inefficient, and many of the later ones are difficult to implement, and so AC-3 is the one most often taught and used in very simple constraint solvers. The AC-3 algorithm is not to be confused with the similarly named A3C algorithm in machine learning. [1]
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.
Variable elimination and the simplex algorithm are used for solving linear and polynomial equations and inequalities, and problems containing variables with infinite domain. These are typically solved as optimization problems in which the optimized function is the number of violated constraints.
In computer science, communicating sequential processes (CSP) is a formal language for describing patterns of interaction in concurrent systems. [1] It is a member of the family of mathematical theories of concurrency known as process algebras, or process calculi, based on message passing via channels.
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.
As a result, the original problem can be solved by first translating it and then solving the resulting problem; however, this algorithm is polynomial-time only if the decomposition does not increase size superpolynomially. The width of a decomposition method is a measure of the size of problem it produced. Originally, the width was defined as ...