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