Tradução e análise de palavras por inteligência artificial ChatGPT
Nesta página você pode obter uma análise detalhada de uma palavra ou frase, produzida usando a melhor tecnologia de inteligência artificial até o momento:
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- é usado com mais frequência na fala oral ou escrita
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- etimologia
O que (quem) é stochastic complexity - definição
![strings]] ''s'', ordered by length; the vertical axis ([[linear scale]]) measures Kolmogorov complexity in [[bit]]s. Most strings are incompressible, i.e. their Kolmogorov complexity exceeds their length by a constant amount. 9 compressible strings are shown in the picture, appearing as almost vertical slopes. Due to Chaitin's incompleteness theorem (1974), the output of any program computing a lower bound of the Kolmogorov complexity cannot exceed some fixed limit, which is independent of the input string ''s''.](https://commons.wikimedia.org/wiki/Special:FilePath/Kolmogorov complexity and computable lower bounds svg.svg?width=200 "strings]] ''s'', ordered by length; the vertical axis ([[linear scale]]) measures Kolmogorov complexity in [[bit]]s. Most strings are incompressible, i.e. their Kolmogorov complexity exceeds their length by a constant amount. 9 compressible strings are shown in the picture, appearing as almost vertical slopes. Due to Chaitin's incompleteness theorem (1974), the output of any program computing a lower bound of the Kolmogorov complexity cannot exceed some fixed limit, which is independent of the input string ''s''.")
In algorithmic information theory (a subfield of computer science and mathematics), the Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer program (in a predetermined programming language) that produces the object as output. It is a measure of the computational resources needed to specify the object, and is also known as algorithmic complexity, Solomonoff–Kolmogorov–Chaitin complexity, program-size complexity, descriptive complexity, or algorithmic entropy. It is named after Andrey Kolmogorov, who first published on the subject in 1963 and is a generalization of classical information theory.
The notion of Kolmogorov complexity can be used to state and prove impossibility results akin to Cantor's diagonal argument, Gödel's incompleteness theorem, and Turing's halting problem. In particular, no program P computing a lower bound for each text's Kolmogorov complexity can return a value essentially larger than P's own length (see section § Chaitin's incompleteness theorem); hence no single program can compute the exact Kolmogorov complexity for infinitely many texts.
Wikipédia
In algorithmic information theory (a subfield of computer science and mathematics), the Kolmogorov complexity of an object, such as a piece of text, is the length of a shortest computer program (in a predetermined programming language) that produces the object as output. It is a measure of the computational resources needed to specify the object, and is also known as algorithmic complexity, Solomonoff–Kolmogorov–Chaitin complexity, program-size complexity, descriptive complexity, or algorithmic entropy. It is named after Andrey Kolmogorov, who first published on the subject in 1963 and is a generalization of classical information theory.
The notion of Kolmogorov complexity can be used to state and prove impossibility results akin to Cantor's diagonal argument, Gödel's incompleteness theorem, and Turing's halting problem. In particular, no program P computing a lower bound for each text's Kolmogorov complexity can return a value essentially larger than P's own length (see section § Chaitin's incompleteness theorem); hence no single program can compute the exact Kolmogorov complexity for infinitely many texts.
