Computer Sciences

Teaching AI agents to type on a Braille keyboard

In recent years, computer scientists have developed artificial intelligence-based techniques that can complete a wide variety of tasks. Some of these techniques are designed to artificially replicate the human senses, particularly ...

Computer Sciences

HAMLET: A platform to simplify AI research and development

Machine learning (ML) algorithms have proved to be highly valuable computational tools for tackling a variety of real-world problems, including image, audio and text classification tasks. Computer scientists worldwide are ...

Computer Sciences

A machine leaning model that incorporates immunological knowledge

The complex network of interconnected cellular signals produced in response to changes in the human body offers a vast amount of interesting and valuable insight that could inform the development of more effective medical ...

Computer Sciences

A heuristic search algorithm to plan attacks in robotic football

Robots have gradually been making their way into a variety of fields and settings, including sports competitions. Robotic football, or soccer, is an innovative version of soccer in which human players are replaced by robots.

Computer Sciences

A 26-layer convolutional neural network for human action recognition

Deep learning algorithms, such as convolutional neural networks (CNNs), have achieved remarkable results on a variety of tasks, including those that involve recognizing specific people or objects in images. A task that computer ...

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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.

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