About: HyperNEAT

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Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (NEAT) algorithm developed by Kenneth Stanley. It is a novel technique for evolving large-scale neural networks using the geometric regularities of the task domain. It uses Compositional Pattern Producing Networks (CPPNs), which are used to generate the images for Picbreeder.org and shapes for EndlessForms.com. HyperNEAT has recently been extended to also evolve plastic ANNs and to evolve the location of every neuron in the network.

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rdf:type	yago:WikicatArtificialNeuralNetworks yago:Abstraction100002137 yago:Act100030358 yago:Activity100407535 yago:Algorithm105847438 yago:Communication100033020 yago:ComputerArchitecture106725249 yago:Description106724763 yago:Event100029378 yago:Message106598915 yago:NeuralNetwork106725467 yago:Procedure101023820 yago:PsychologicalFeature100023100 yago:WikicatGeneticAlgorithms yago:YagoPermanentlyLocatedEntity yago:Rule105846932 yago:Specification106725067 yago:Statement106722453 yago:WikicatEvolutionaryAlgorithms
rdfs:label	HyperNEAT (fr) HyperNEAT (en)
rdfs:comment	Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (NEAT) algorithm developed by Kenneth Stanley. It is a novel technique for evolving large-scale neural networks using the geometric regularities of the task domain. It uses Compositional Pattern Producing Networks (CPPNs), which are used to generate the images for Picbreeder.org and shapes for EndlessForms.com. HyperNEAT has recently been extended to also evolve plastic ANNs and to evolve the location of every neuron in the network. (en) Le NEAT basé sur l'hypercube, ou HyperNEAT est un codage génératif pour évoluer des réseaux de neurones artificiels (ANN) avec les principes de l'algorithme NeuroEvolution of Augmented Topologies (NEAT) développé par Kenneth Stanley. Il s'agit d'une nouvelle technique pour faire évoluer des réseaux de neurones à grande échelle en utilisant les régularités géométriques du domaine de la tâche. (fr)
foaf:depiction
dcterms:subject	Evolutionary computation Genetic algorithms Artificial neural networks Evolutionary algorithms
Wikipage page ID	21573718 (xsd:integer)
Wikipage revision ID	1092358706 (xsd:integer)
Link from a Wikipage to another Wikipage	Artificial neural networks Evolutionary computation Genetic algorithms Kenneth Stanley Artificial neural networks Evolutionary algorithms CPPN NeuroEvolution of Augmented Topologies
Link from a Wikipage to an external page	http://EndlessForms.com http://www.picbreeder.org http://beacon-center.org/blog/2012/08/13/evolution-101-neuroevolution/ http://www.cs.ucf.edu/~kstanley/neat.html http://eplex.cs.ucf.edu/hyperNEATpage/HyperNEAT.html http://www.cs.ucf.edu/~kstanley/ http://PicBreeder.org http://eplex.cs.ucf.edu https://www.youtube.com/watch%3Fv=V2ADU8YWIug
sameAs	HyperNEAT HyperNEAT HyperNEAT HyperNEAT HyperNEAT
dbp:wikiPageUsesTemplate	dbt:Reflist dbt:Bioinformatics-stub
thumbnail	wiki-commons:Special:FilePath/HyperNEAT_query_connection.png?width=300
has abstract	Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves artificial neural networks (ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (NEAT) algorithm developed by Kenneth Stanley. It is a novel technique for evolving large-scale neural networks using the geometric regularities of the task domain. It uses Compositional Pattern Producing Networks (CPPNs), which are used to generate the images for Picbreeder.org and shapes for EndlessForms.com. HyperNEAT has recently been extended to also evolve plastic ANNs and to evolve the location of every neuron in the network. (en) Le NEAT basé sur l'hypercube, ou HyperNEAT est un codage génératif pour évoluer des réseaux de neurones artificiels (ANN) avec les principes de l'algorithme NeuroEvolution of Augmented Topologies (NEAT) développé par Kenneth Stanley. Il s'agit d'une nouvelle technique pour faire évoluer des réseaux de neurones à grande échelle en utilisant les régularités géométriques du domaine de la tâche. L'encodage génétique est indirect. L'algorithme utilise des réseaux de production de motifs de composition ( CPPN ), qui sont utilisés pour générer les images pour Picbreeder.org et les formes pour EndlessForms.com. HyperNEAT a récemment été étendu pour faire évoluer également des réseaux de neurones artificiel plastique et pour faire évoluer l'emplacement de chaque neurone du réseau. (fr)
prov:wasDerivedFrom	wikipedia-en:HyperNEAT?oldid=1092358706&ns=0
page length (characters) of wiki page	10337 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:HyperNEAT
is Link from a Wikipage to another Wikipage of	Compositional pattern-producing network Kenneth Stanley Hyperneat Neuroevolution Neuroevolution of augmenting topologies
is Wikipage redirect of	Hyperneat
is foaf:primaryTopic of	wikipedia-en:HyperNEAT

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