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In artificial intelligence and operations … In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. A solution is therefore a set of values for the variables that satisfies all constraints—that is, a point in the feasible region. The techniques used in constraint satisfaction depend on the kind of constraints being considered. Often used are constraints on a finite domain, to the point that constraint satisfaction problems are typically identified with problems based on constraints on a finite domain. Such problems are usually solved via search, in particular a form of backtracking or local search. Constraint propagation are other methods used on such problems; most of them are incomplete in general, that is, they may solve the problem or prove it unsatisfiable, but not always. Constraint propagation methods are also used in conjunction with search to make a given problem simpler to solve. Other considered kinds of constraints are on real or rational numbers; solving problems on these constraints is done via variable elimination or the simplex algorithm. Constraint satisfaction as a general problem originated in the field of artificial intelligence in the 1970s (see for example). However, when the constraints are expressed as multivariate linear equations defining (in)equalities, the field goes back to Joseph Fourier in the 19th century: George Dantzig's invention of the Simplex Algorithm for Linear Programming (a special case of mathematical optimization) in 1946 has allowed determining feasible solutions to problems containing hundreds of variables. During the 1980s and 1990s, embedding of constraints into a programming language were developed. The first languages devised expressly with intrinsic support for constraint programming was Prolog. Since then, constraint-programming libraries have become available in other languages, such as C++ or Java (e.g., Choco for Java).uch as C++ or Java (e.g., Choco for Java).
, Em inteligência artificial e investigação … Em inteligência artificial e investigação operacional, satisfação de restrições é um processo de encontrar a solução para um conjunto de restrições que impõe uma série de condições para que variáveis possam ser atendidas. Uma solução é portanto um conjunto de valores que satisfazem as variáveis de forma a atender todas as restrições que existem para o mundo em que se encontram. As técnicas usadas na resolução de problemas de satisfação de restrições dependem do tipo de restrição inicial que é considerada. Geralmente ocorre o uso de restrições sobre um domínio finito de forma que o problema de satisfação de restrições e identificável como um problema baseado em restrições deste conjunto finito de restrições. Tais problemas são normalmente resolvidos pela execução de um algoritmo de busca, em particular por algoritmos de backtracking ou busca local. Métodos de consistência local também são empregados para tais problemas, e de forma geral tais algoritmos são incompletos. Ou seja eles podem resolver o problema de provar a insatisfabilidade de um conjunto, mas nem sempre são capazes de executar tal operação. A técnica de consistência local também é usada em conjunto com algoritmos de busca para tornar o problema mais simples de ser resolvido. Outros tipos de restrição a serem considerados são os relacionados sob a forma de números reais e racionais; uma vez que, a resolução de problemas nestes mundos é feita por meio da eliminação de variáveis ou do algoritmo simplex. Satisfação de restrições se originou como um campo da inteligência artificial em meados de 1970. Durante as décadas de 1980 e 1990, foram desenvolvidas a inclusão de tal teoria em linguagens de programação como Prolog e C++.nguagens de programação como Prolog e C++.
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In artificial intelligence and operations … In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through a set of constraints that impose conditions that the variables must satisfy. A solution is therefore a set of values for the variables that satisfies all constraints—that is, a point in the feasible region.s—that is, a point in the feasible region.
, Em inteligência artificial e investigação … Em inteligência artificial e investigação operacional, satisfação de restrições é um processo de encontrar a solução para um conjunto de restrições que impõe uma série de condições para que variáveis possam ser atendidas. Uma solução é portanto um conjunto de valores que satisfazem as variáveis de forma a atender todas as restrições que existem para o mundo em que se encontram. existem para o mundo em que se encontram.
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Satisfação de restrições
, Constraint satisfaction
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