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Neuroevolution of Augmenting Topologies Demos (2003)
Author: Kenneth Stanley
The NEAT Demo Page contains several examples of complex, interesting behaviors evolved using Neuroevolution of Augmenting Topologies (NEAT).
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People
Kenneth Stanley Postdoctoral Alumni kstanley [at] cs ucf edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Projects
NEAT: Evolving Increasingly Complex Neural Network Topologies 2000 - 2011
Publications
Coevolution of Neural Networks using a Layered Pareto Archive German A. Monroy, Kenneth O. Stanley, Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference, 329-336, Seattle, Wash... 2006
Competitive Coevolution through Evolutionary Complexification Kenneth O. Stanley and Risto Miikkulainen Journal of Artificial Intelligence Research, 21:63-100, 2004. 2004
Evolving Neural Networks Through Augmenting Topologies Kenneth O. Stanley and Risto Miikkulainen Evolutionary Computation, 10(2):99-127, 2002. 2002
IJCNN-2013 Tutorial on Evolution of Neural Networks Risto Miikkulainen To Appear In 2013. Tutorial slides.. 2013
Software/Data
NEAT C# The SharpNEAT package contains C# source code for the NeuroEvolution of Augmenting Topologies method (see the original <... 2003
NEAT C++ for Microsoft Windows The Windows NEAT package contains C++ source code for the NeuroEvolution of Augmenting Topologies method (see the origin... 2002
NEAT C++ The NEAT package contains source code implementing the NeuroEvolution of Augmenting Topologies method. The source code i... 2010
NEAT Delphi The Delphi NEAT package contains Delphi source code for the NeuroEvolution of Augmenting Topologies method (see the orig... 2003
NEAT Java (JNEAT) The JNEAT package contains Java source code for the NeuroEvolution of Augmenting Topologies method (see the original 2002
NEAT Matlab The Matlab NEAT package contains Matlab source code for the NeuroEvolution of Augmenting Topologies method (see the orig... 2003
NEAT: ANJI (Another NEAT Java Implementation) The ANJI package contains Java source code for the NeuroEvolution of Augmenting Topologies method (see the original 2004
Areas of Interest
Neuroevolution Reinforcement Learning
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