HyperNEAT
Encyclopedia
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. It is a novel technique for evolving large-scale neural networks utilizing 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 EndlessForms.com.
NeuroEvolution of Augmented Topologies
NeuroEvolution of Augmenting Topologies is a genetic algorithm for the generation of evolving artificial neural networks developed by Ken Stanley in 2002 while at The University of Texas at Austin...
(NEAT) algorithm. It is a novel technique for evolving large-scale neural networks utilizing 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 EndlessForms.com.
Applications to Date
- Multi-agent learning
- Checkers board evaluation
- Controlling Legged Robots
- Comparing Generative vs. Direct Encodings
- Investigating the Evolution of Modular Neural Networks