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In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, causal inference, etc.
Computer engineering is a branch of computer science and electronic engineering that integrates several fields of computer science and electronic engineering required to develop computer hardware and software. Computer engineering is referred to as computer science and engineering at some universities.
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High-level synthesis (HLS), sometimes referred to as C synthesis, electronic system-level (ESL) synthesis, algorithmic synthesis, or behavioral synthesis, is an automated design process that takes an abstract behavioral specification of a digital system and finds a register-transfer level structure that realizes the given behavior.
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A Hardware Trojan (HT) is a malicious modification of the circuitry of an integrated circuit. A hardware Trojan is completely characterized by its physical representation and its behavior. The payload of an HT is the entire activity that the Trojan executes when it is triggered. In general, Trojans try to bypass or disable the security fence of a system: for example, leaking confidential information by radio emission. HTs also could disable, damage or destroy the entire chip or components of it.
Natural computing, also called natural computation, is a terminology introduced to encompass three classes of methods: 1) those that take inspiration from nature for the development of novel problem-solving techniques; 2) those that are based on the use of computers to synthesize natural phenomena; and 3) those that employ natural materials to compute. The main fields of research that compose these three branches are artificial neural networks, evolutionary algorithms, swarm intelligence, artificial immune systems, fractal geometry, artificial life, DNA computing, and quantum computing, among others.
Artificial life is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. The discipline was named by Christopher Langton, an American theoretical biologist, in 1986. In 1987, Langton organized the first conference on the field, in Los Alamos, New Mexico. There are three main kinds of alife, named for their approaches: soft, from software; hard, from hardware; and wet, from biochemistry. Artificial life researchers study traditional biology by trying to recreate aspects of biological phenomena.
References
- ↑ Thompson, Adrian (1997). "An evolved circuit, intrinsic in silicon, entwined with physics". Evolvable Systems: From Biology to Hardware. Lecture Notes in Computer Science. Vol. 1259. pp. 390–405. CiteSeerX 10.1.1.50.9691 . doi:10.1007/3-540-63173-9_61. ISBN 978-3-540-63173-6.
- ↑ Garvie, Michael; Husbands, Phil (2019). "Automatic Synthesis of Totally Self-Checking Circuits" . Retrieved 29 November 2021.
- ↑ Garvie, Michael; Thompson, Adrian (2021). "Low Overhead Self-Checking Combinational and Sequential Circuits Designed by Evolution" . Retrieved 29 November 2021.