NeuroEvolution by Augmented Topologies

Neuro-Evolution of Augmenting Topologies (NEAT) is a genetic algorithm for evolving neural networks written by Ken Stanley at University of Texas at Austin and published under the GPL; it integrates with Guile, a GNU common lisp interpreter.

External links

• Ken Stanley's website
• NEAT Homepage
• Evolving Adaptive Neural Networks with and without Adaptive Synapses
• download NEAT 1.1

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