Lower semicomputable function: Difference between revisions
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* for all <math>x \in X</math> and all natural numbers <math>n</math>, we have <math>g(x, n+1) \geq g(x,n)</math> | * for all <math>x \in X</math> and all natural numbers <math>n</math>, we have <math>g(x, n+1) \geq g(x,n)</math> | ||
* for all <math>x \in X</math> we have <math>\lim_{n\to \infty} g(x,n) = f(x)</math> | * for all <math>x \in X</math> we have <math>\lim_{n\to \infty} g(x,n) = f(x)</math> | ||
(i think X might have to be a recursive set) | |||
The way to think of this is that given some fixed <math>x \in X</math>, the values <math>g(x,0), g(x,1), g(x,2), \ldots</math> are successive approximations of the value <math>f(x)</math>, and we have <math>g(x,0) \leq g(x,1) \leq g(x,2) \leq \cdots \leq f(x)</math>. | The way to think of this is that given some fixed <math>x \in X</math>, the values <math>g(x,0), g(x,1), g(x,2), \ldots</math> are successive approximations of the value <math>f(x)</math>, and we have <math>g(x,0) \leq g(x,1) \leq g(x,2) \leq \cdots \leq f(x)</math>. | ||
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If we do not know the value of <math>f(x)</math> in advance, it is not possible to tell in general how far away <math>g(x,n)</math> is from <math>f(x)</math>. We would know that <math>g(x,1000)</math> is at least as close to <math>f(x)</math> as <math>g(x,100)</math>, but it's not clear how much closer. In contrast, if a function is both lower and upper semicomputable, then we would have an approximation from above, say <math>h(x,n)</math>. Then <math>g(x,n) \leq f(x) \leq h(x,n)</math>, so we have an estimate that is off by at most <math>h(x,n)-g(x,n)</math>. | If we do not know the value of <math>f(x)</math> in advance, it is not possible to tell in general how far away <math>g(x,n)</math> is from <math>f(x)</math>. We would know that <math>g(x,1000)</math> is at least as close to <math>f(x)</math> as <math>g(x,100)</math>, but it's not clear how much closer. In contrast, if a function is both lower and upper semicomputable, then we would have an approximation from above, say <math>h(x,n)</math>. Then <math>g(x,n) \leq f(x) \leq h(x,n)</math>, so we have an estimate that is off by at most <math>h(x,n)-g(x,n)</math>. | ||
Lower semicomputability can be characterized using the idea of recursive enumerability as follows: <math>f : X \to \mathbf R</math> is lower semicomputable if and only if the set <math>\{(x,q) \in X \times \mathbf Q : f(x) > q\}</math> is recursively enumerable. | |||
Examples: | |||
* Every computable function is lower semicomputable (Why?) | |||
* Kolmogorov complexity? | |||
Latest revision as of 06:03, 25 July 2019
A function is lower semicomputable iff there exists a computable function such that:
- for all and all natural numbers , we have
- for all we have
(i think X might have to be a recursive set)
The way to think of this is that given some fixed , the values are successive approximations of the value , and we have .
The definition says nothing about the rate of convergence, so for instance if we want to be within of the value of , there is not in general some way to find a large enough .
If we do not know the value of in advance, it is not possible to tell in general how far away is from . We would know that is at least as close to as , but it's not clear how much closer. In contrast, if a function is both lower and upper semicomputable, then we would have an approximation from above, say . Then , so we have an estimate that is off by at most .
Lower semicomputability can be characterized using the idea of recursive enumerability as follows: is lower semicomputable if and only if the set is recursively enumerable.
Examples:
- Every computable function is lower semicomputable (Why?)
- Kolmogorov complexity?