Term  Brief description  Charts 

genetic algorithm 
A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover. (Excerpt from <a href="http://en.wikipedia.org/wiki/Genetic_algorithm">Wikipedia article: Genetic algorithm</a>) Percentage of Ariadne articles tagged with this term: [term_node_prcnt_1]%. 

algorithm 
In mathematics and computer science, an algorithm is an effective method expressed as a finite list of welldefined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning. In simple words an algorithm is a stepbystep procedure for calculations. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, will proceed through a finite number of welldefined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input. (Excerpt from <a href="http://en.wikipedia.org/wiki/Algorithm">Wikipedia article: Algotithm</a>) Percentage of Ariadne articles tagged with this term: [term_node_prcnt_1]%. 
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