Hypercube-based NEAT, or HyperNEAT, is a generative encoding that evolves

artificial neural networks Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected unit ...

(ANNs) with the principles of the widely used NeuroEvolution of Augmented Topologies (NEAT) algorithm developed by

Kenneth Stanley Kenneth Owen Stanley is an artificial intelligence researcher, author, and former professor of computer science at the University of Central Florida known for creating the Neuroevolution of augmenting topologies (NEAT) algorithm. He coauthored ''W ...

. 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 fo
Picbreeder.org
and shapes fo
EndlessForms.com
. HyperNEAT has recently been extended to also evolve plastic ANNs and to evolve the location of every neuron in the network.

Applications to date

* Multi-agent learning * Checkers board evaluation * Controlling Legged Robo
video
* Comparing Generative vs. Direct Encodings * Investigating the Evolution of Modular Neural Networks * Evolving Objects that can be 3D-printed * Evolving the Neural Geometry and Plasticity of an ANN

References

External links

Ken Stanley's website"Evolutionary Complexity Research Group at UCF"PicBreeder.org

EndlessForms.com
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BEACON Blog: What is neuroevolution?
Artificial neural networks Evolutionary algorithms Evolutionary computation Genetic algorithms