Examples of using Computable functions in English and their translations into Greek
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Computable Functions.
Characteristics of computable functions.
Computable functions are the basic objects of study in computability theory.
This term has since come to be identified with the computable functions.
The class of computable functions can be defined in many equivalent models of computation, including.
In recursion theory, 0 can be used to denote the Turing degree of the partial computable functions.
A Blum complexity measure is defined using computable functions without any reference to a specific model of computation.
Numberings can be partial-recursive although some of its members are total recursive,that is, computable functions.
Computable functions are used to discuss computability without referring to any concrete model of computation such as Turing machines or register machines.
For a total computable function f{\displaystyle f} complexity classes of computable functions can be defined as.
The fundamental results establish a robust, canonical class of computable functions with numerous independent, equivalent characterizations using Turing machines, λ calculus, and other systems.
The Blum axioms can be used to define an abstract computational complexity theory on the set of computable functions.
Particular models of computability that give rise to the set of computable functions are the Turing-computable functions and the μ-recursive functions. .
Furthermore, this procedure has to be encoded in the finite alphabet used by the computational model,so there are only countably many computable functions.
Equivalently, computable functions can be formalized as functions which can be calculated by an idealized computing agent such as a Turing machine or a register machine.
Basic results are that all recursively enumerable classes of functions are learnable while the class REC of all computable functions is not learnable.
In agreement with this definition,the remainder of this article presumes that computable functions take finitely many natural numbers as arguments and produce a value which is a single natural number.
In computational complexity theory the Blum axioms orBlum complexity axioms are axioms that specify desirable properties of complexity measures on the set of computable functions.
The general scenario is the following:Given a class S of computable functions, is there a learner(that is, recursive functional) which outputs for any input of the form f(0), f(1 f(n)) a hypothesis.
This approach led him to suggest a definition of randomness thatwas later refined and made mathematically rigorous by Alonzo Church by using computable functions in 1940.
C( f){\displaystyle C(f)} is the set of all computable functions with a complexity less than f{\displaystyle f}. C 0( f){\displaystyle C^{0}(f)} is the set of all boolean-valued functions with a complexity less than f{\displaystyle f}.
For example, if the formalism lets algorithms define functions over strings(such as Turing machines) then there should be a mapping of these algorithms to strings, andif the formalism lets algorithms define functions over natural numbers(such as computable functions) then there should be a mapping of algorithms to natural numbers.
According to the Church- Turing thesis, computable functions are exactly the functions that can be calculated using a mechanical calculation device given unlimited amounts of time and storage space.
With more rigor, a function is computable if and only if there is an effective procedure that, given any k-tuple of natural numbers, will produce the value.[1] In agreement with this definition,the remainder of this article presumes that computable functions take finitely many natural numbers as arguments and produce a value which is a single natural number.
According to the Church- Turing thesis, computable functions are exactly the functions that can be calculated using a mechanical calculation device given unlimited amounts of time and storage space.
The class of computable functions can be defined in many equivalent models of computation, including Turing machines μ-recursive functions Lambda calculus Post machines(Post- Turing machines and tag machines).
Recursion theory, also called computability theory,studies the properties of computable functions and the Turing degrees, which divide the uncomputable functions into sets that have the same level of uncomputability.
Computable functions are the formalized analogue of the intuitive notion of algorithm, in the sense that a function is computable if there exists an algorithm that can do the job of the function, i.e. given an input of the function domain it can return the corresponding output.
Although the Church- Turing thesis states that the computable functions include all functions with algorithms, it is possible to consider broader classes of functions that relax the requirements that algorithms must possess.
For example, one can formalize computable functions as μ-recursive functions, which are partial functions that take finite tuples of natural numbers and return a single natural number(just as above).