algorithmes & Métaheuristique
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Note that descriptions are picked up from the web sites of the projects.
One of the scientist key policy is always to refer to people who did the first work (as it is pointed out by the "hard blogging scientists" manifest ).
NeuroEvolution of Augmenting Topologies ( NEAT ) is a genetic algorithm for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Ken Stanley in 2002 while at The University of Texas at Austin .
Hypercube-based NEAT , or HyperNEAT , [ 1 ] is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (NEAT) algorithm. [ 2 ] It is a novel technique for evolving large-scale neural networks utilizing the geometric regularities of the task domain.
"To achieve your highest goals, you must be willing to abandon them."
Compositional pattern-producing networks (CPPNs) , are a variation of artificial neural networks (ANNs) which differ in their set of activation functions and how they are applied.
Evolutionary art is created using a computer.
In artificial intelligence , an evolutionary algorithm (EA) is a subset of evolutionary computation , a generic population-based metaheuristic optimization algorithm . An EA uses mechanisms inspired by biological evolution , such as reproduction , mutation , recombination , and selection . Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the environment within which the solutions "live" (see also cost function ).
Un article de Wikipédia, l'encyclopédie libre.
Un article de Wikipédia, l'encyclopédie libre. La recherche tabou est une métaheuristique d'optimisation présentée par Fred Glover en 1986.
Un article de Wikipédia, l'encyclopédie libre. Une métaheuristique est un algorithme d’ optimisation visant à résoudre des problèmes d’ optimisation difficile (souvent issus des domaines de la recherche opérationnelle , de l' ingénierie ou de l' intelligence artificielle ) pour lesquels on ne connaît pas de méthode classique plus efficace.
In computer science , a binary search or half-interval search algorithm finds the position of a specified value (the input "key") within a sorted array . [ 1 ] [ 2 ] In each step, the algorithm compares the input key value with the key value of the middle element of the array.