algorithmes & Métaheuristique
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Handbook of Algorithms and Data Structures
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algorithm
Dreaming of Metaheuristics
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
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.
HyperNEAT
Compositional pattern-producing network
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 algorithm
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.
Théorie de la complexité des algorithmes
Un article de Wikipédia, l'encyclopédie libre. La recherche tabou est une métaheuristique d'optimisation présentée par Fred Glover en 1986.
Recherche tabou
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.