augmenting$509037$ - traducción al holandés
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augmenting$509037$ - traducción al holandés

GENETIC ALGORITHM FOR THE GENERATION OF EVOLVING ARTIFICIAL NEURAL NETWORKS DEVELOPED BY KEN STANLEY IN 2002
NeuroEvolution by Augmented Topologies; NeuroEvolution of Augmented Topologies; NeuroEvolution of Augmenting Topologies

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Definición

data structure
<data, programming> Any method of organising a collection of data to allow it to be manipulated effectively. It may include meta data to describe the properties of the structure. Examples data structures are: array, dictionary, graph, hash, heap, linked list, matrix, object, queue, ring, stack, tree, vector. (2003-09-11)

Wikipedia

Neuroevolution of augmenting topologies

NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm (GA) for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Kenneth Stanley and Risto Miikkulainen in 2002 while at The University of Texas at Austin. It alters both the weighting parameters and structures of networks, attempting to find a balance between the fitness of evolved solutions and their diversity. It is based on applying three key techniques: tracking genes with history markers to allow crossover among topologies, applying speciation (the evolution of species) to preserve innovations, and developing topologies incrementally from simple initial structures ("complexifying").