Neuroevolution of augmenting topologies information
Genetic algorithm for making artificial neural networks
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").
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computation NeuroEvolutionofAugmentingTopologies (NEAT) HyperNEAT (A Generative version of NEAT) Evolutionary Acquisition of Neural Topologies (EANT/EANT2)...
former professor of computer science at the University of Central Florida known for creating the Neuroevolutionofaugmentingtopologies (NEAT) algorithm...
Records, a British record label Neuroevolutionofaugmentingtopologies (NEAT), a genetic algorithm (GA) for the generation of evolving artificial neural networks...
JPL to discover near-Earth objects Neuroevolutionofaugmentingtopologies, a genetic algorithm for the generation of evolving artificial neural networks...
that plays Super Mario World. The program is based on neuroevolutionofaugmentingtopologies; thus, it generates neural networks using genetic algorithms...
IEEE Transactions on Neural Networks, 5:54–65, 1994. [1] NeuroEvolutionofAugmentedTopologies (NEAT) by Stanley and Miikkulainen, 2005 [2] Yohannes Kassahun...
artificial neural networks (ANNs) with the principles of the widely used NeuroEvolutionofAugmentedTopologies (NEAT) algorithm developed by Kenneth Stanley...
connect the outputs of all neurons to the inputs of all neurons. This is the most general neural network topology because all other topologies can be represented...
the population into subpopulations (or species) but employs the space topology instead is proposed in. Wong, K. C. (2015), Evolutionary Multimodal Optimization:...
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