Neuroevolution of Augmenting Topologies (NEAT) is an
evolutionary algorithm for evolving artificial neural networks.
SharpNEAT is an implementation of NEAT written in C# / .NET
- Equations of Motion for the Cart and Pole Control Task (2020)
- A Review of Activation Functions in SharpNEAT (2017)
- Efficacy Sampling (2017)
- Phased Searching with NEAT: Alternating Between Complexification And Simplification (2004)
- Speciation in Canonical NEAT (2009)
- Speciation with K-Means Clustering (2009)
- A Neural Network Controller for the Physical Travelling Saleperson Problem (2005)
- An Integer Based Neural Network (2004)
Genetic Art with SharpNEAT. Holger Ferstl created this SharpNEAT based application that evolves images by allowing a user to iteratively select their favourite from a page of candidate images.
Below is a selection of images created using this application; more images can be seen via Holger's blog post (via the above link).
