Lower semicomputable function: Difference between revisions

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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.
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?

Revision as of 06:00, 25 July 2019

A function f:XR is lower semicomputable iff there exists a computable function g:X×NQ such that:

  • for all xX and all natural numbers n, we have g(x,n+1)g(x,n)
  • for all xX we have limng(x,n)=f(x)

The way to think of this is that given some fixed xX, the values g(x,0),g(x,1),g(x,2), are successive approximations of the value f(x), and we have g(x,0)g(x,1)g(x,2)f(x).

The definition says nothing about the rate of convergence, so for instance if we want g(x,n) to be within 1/1000 of the value of f(x), there is not in general some way to find a large enough n.

If we do not know the value of f(x) in advance, it is not possible to tell in general how far away g(x,n) is from f(x). We would know that g(x,1000) is at least as close to f(x) as g(x,100), 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 h(x,n). Then g(x,n)f(x)h(x,n), so we have an estimate that is off by at most h(x,n)g(x,n).

Lower semicomputability can be characterized using the idea of recursive enumerability as follows: f:XR is lower semicomputable if and only if the set {(x,q)X×Q:f(x)>q} is recursively enumerable.

Examples:

  • Every computable function is lower semicomputable (Why?)
  • Kolmogorov complexity?