Related topics: google · robot · search engine

Rethinking spin chemistry from a quantum perspective

Researchers at Osaka City University use quantum superposition states and Bayesian inference to create a quantum algorithm, easily executable on quantum computers, that accurately and directly calculates energy differences ...

Artificial intelligence beats us in chess, but not in memory

In the last decades, artificial intelligence has shown to be very good at achieving exceptional goals in several fields. Chess is one of them: in 1996, for the first time, the computer Deep Blue beat a human player, chess ...

AI-powered microscope could check cancer margins in minutes

When surgeons remove cancer, one of the first questions is, "Did they get it all?" Researchers from Rice University and the University of Texas MD Anderson Cancer Center have created a new microscope that can quickly and ...

"Big data" enables first census of desert shrub

The creosote is the king of the desert. This scraggly shrub dominates the landscape of the American southwest, creating mini-oases from the harsh heat for desert wildlife.

Algorithm could identify disease-associated genes

ITMO University's bioinformatics researchers have developed an algorithm that helps to assess the influence of genes on processes in the human body, including the development of disease. The research was published in BMC ...

page 1 from 40


In mathematics, computing, linguistics, and related subjects, an algorithm is a finite sequence of instructions, an explicit, step-by-step procedure for solving a problem, often used for calculation and data processing. It is formally a type of effective method in which a list of well-defined instructions for completing a task, will when given an initial state, proceed through a well-defined series of successive states, eventually terminating in an end-state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as probabilistic algorithms, incorporate randomness.

A partial formalization of the concept began with attempts to solve the Entscheidungsproblem (the "decision problem") posed by David Hilbert in 1928. Subsequent formalizations were framed as attempts to define "effective calculability" (Kleene 1943:274) or "effective method" (Rosser 1939:225); those formalizations included the Gödel-Herbrand-Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church's lambda calculus of 1936, Emil Post's "Formulation 1" of 1936, and Alan Turing's Turing machines of 1936–7 and 1939.

This text uses material from Wikipedia, licensed under CC BY-SA