What is algorithmic complexity?

algorithmic complexity (computational complexity or perpendicular complexity) is the basic idea in the theory of theory of computational complexity and algorithmic information theory and plays an important role in formal induction.

The algorithmic complexity of the binary chain is defined as the shortest and most effective program that can create a string. Although there are an endless number of programs that can create any given string, one program or a group of programs will always be the shortest. There is no algorithmic way to find the shortest algorithm that gives a given string; This is one of the first results of the theory of computing complexity. Yet we can make an educated estimate. This result (computing complexity of the chain) will prove to be very important for evidence regarding computational. In fact, a reduction in the complexity of real objects to programs that produce objects as output, one way to view POut of science. The complex objects around us tend to come from three main generation processes; origin , evolution and intelligence , with objects produced every tendency to greater algorithmic complexity.

Computational complexity is an idea that is often used in theoretical computer science to determine the relative difficulty of calculating the solution of wide classes of mathematical and logical problems. There are more than 400 classes of complexity and other classes are constantly appearing. Famous p = NP The question concerns the nature of two of these classes of complexity. Class of complexity includes problems much more difficult than other can be confronted in mathematics up to number. There are many imaginable problems in the theory of computing complexity that would require a solution to almost endless time.

algorithmic complexity and related concepts were developed in the 60s of dozens of sciencesců. Andrey Kolmogorov, Ray Solomonoff and Gregory Chaitin at the end of the 60s have contributed significantly to algorithmic information theory. The principle of minimum report length, closely related to algorithmic complexity, provides a large part of the foundations of statistical and inductive inference and machine learning.