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In computability theory, an undecidable problem is a decision problem for which an effective method (algorithm) to derive the correct answer does not exist. More formally, an undecidable problem is a problem whose language is not a recursive set ; see the article Decidable language .
This problem is usually called the linear search problem and a search plan is called a trajectory. The linear search problem for a general probability distribution is unsolved. [ 5 ] However, there exists a dynamic programming algorithm that produces a solution for any discrete distribution [ 6 ] and also an approximate solution, for any ...
The first three functions have points for which the limit does not exist, while the function = is not defined at =, but its limit does exist. respectively. If these limits exist at p and are equal there, then this can be referred to as the limit of f(x) at p. [7] If the one-sided limits exist at p, but are unequal, then there is no limit at ...
Limits can be difficult to compute. There exist limit expressions whose modulus of convergence is undecidable. In recursion theory, the limit lemma proves that it is possible to encode undecidable problems using limits. [14] There are several theorems or tests that indicate whether the limit exists. These are known as convergence tests.
Many mathematical problems have been stated but not yet solved. These problems come from many areas of mathematics, such as theoretical physics, computer science, algebra, analysis, combinatorics, algebraic, differential, discrete and Euclidean geometries, graph theory, group theory, model theory, number theory, set theory, Ramsey theory, dynamical systems, and partial differential equations.
The adjective indeterminate does not imply that the limit does not exist, as many of the examples above show. In many cases, algebraic elimination, L'Hôpital's rule, or other methods can be used to manipulate the expression so that the limit can be evaluated.
At the line search step (2.3), the algorithm may minimize h exactly, by solving ′ =, or approximately, by using one of the one-dimensional line-search methods mentioned above. It can also be solved loosely , by asking for a sufficient decrease in h that does not necessarily approximate the optimum.
However, some problems have distinct optimal solutions; for example, the problem of finding a feasible solution to a system of linear inequalities is a linear programming problem in which the objective function is the zero function (i.e., the constant function taking the value zero everywhere).