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Like logic programming, narrowing of algebraic value sets gives a method of reasoning about the values in unsolved or partially solved equations. Where logic programming relies on resolution, the algebra of value sets relies on narrowing rules. Narrowing rules allow the elimination of values from a solution set which are inconsistent with the equations being solved. Unlike logic programming, narrowing of algebraic value sets makes no use of backtracking. Instead all values are contained in value sets, and are considered in parallel.

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  • Like logic programming, narrowing of algebraic value sets gives a method of reasoning about the values in unsolved or partially solved equations. Where logic programming relies on resolution, the algebra of value sets relies on narrowing rules. Narrowing rules allow the elimination of values from a solution set which are inconsistent with the equations being solved. Unlike logic programming, narrowing of algebraic value sets makes no use of backtracking. Instead all values are contained in value sets, and are considered in parallel. The approach is also similar to the use of constraints in constraint logic programming, but without the logic processing basis. is a natural extension of value sets to deductive probability. The value set construct holds the information required to calculate probabilities of calculated values based on probabilities of initial values. (en)
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  • Like logic programming, narrowing of algebraic value sets gives a method of reasoning about the values in unsolved or partially solved equations. Where logic programming relies on resolution, the algebra of value sets relies on narrowing rules. Narrowing rules allow the elimination of values from a solution set which are inconsistent with the equations being solved. Unlike logic programming, narrowing of algebraic value sets makes no use of backtracking. Instead all values are contained in value sets, and are considered in parallel. (en)
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  • Narrowing of algebraic value sets (en)
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