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GitHub topics: hyperneat

yaricom/goESHyperNEAT

The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.

Language: Go - Size: 1.39 MB - Last synced at: 19 days ago - Pushed at: about 2 months ago - Stars: 18 - Forks: 2

kgd-al/abrain

ES-HyperNEAT Python implementation with C++ computations for NeuroEvolution, Reinforcement Learning and VfMRI

Language: Python - Size: 805 KB - Last synced at: 29 days ago - Pushed at: about 2 months ago - Stars: 4 - Forks: 1

Boucaa/Crawler

Language: Kotlin - Size: 28.4 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0

cristianglezm/EvoAI

A C++17 library to Evolve (via NEAT and HyperNEAT) / train small Neural Networks.

Language: C++ - Size: 3.82 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

ukuleleplayer/pureples

Pure Python Library for ES-HyperNEAT. Contains implementations of HyperNEAT and ES-HyperNEAT.

Language: Python - Size: 155 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 109 - Forks: 36

gabo-di/DeepHyperNEAT-Julia

A unofficial julia implementation of the DeepHyperNEAT system for evolving neural networks. Written in julia by Gabriel Diaz, developed by Felix Sosa and Kenneth Stanley (all credit goes to them and all blame to me). See paper: https://eplex.cs.ucf.edu/papers/sosa_ugrad_report18.pdf and original code: https://github.com/flxsosa/DeepHyperNEAT

Language: Julia - Size: 53.7 KB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0

flxsosa/DeepHyperNEAT

A public python implementation of the DeepHyperNEAT system for evolving neural networks. Developed by Felix Sosa and Kenneth Stanley. See paper here: https://eplex.cs.ucf.edu/papers/sosa_ugrad_report18.pdf

Language: Python - Size: 1 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 61 - Forks: 16

crisbodnar/TensorFlow-NEAT

TensorFlow Eager implementation of NEAT and Adaptive HyperNEAT

Language: Python - Size: 905 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 116 - Forks: 32

flo-wolf/UnitySharpNEAT

Implementation of SharpNEAT in Unity 2020. Full refactor of the UnityNEAT project.

Language: C# - Size: 4.17 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 29 - Forks: 3

adam-katona/indirect_encoding_maml

This repository contains the code for the paper: Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning

Language: Jupyter Notebook - Size: 460 KB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 2 - Forks: 0

SirBob01/HyperNEAT

C++ ES-HyperNEAT algorithm implementation

Language: C++ - Size: 101 KB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

Fr4ctlize/OxiNEAT

An implementation of NeuroEvolution of Augmenting Topologies, and its later iteration HyperNEAT.

Language: Rust - Size: 313 KB - Last synced at: about 1 month ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0

WatchJolley/river-hyperneat

HyperNEAT experiment for the River Crossing Task

Language: C++ - Size: 95.7 KB - Last synced at: about 2 years ago - Pushed at: about 5 years ago - Stars: 0 - Forks: 0

gerich-home/neuro-evolution-knowledge-base

My thougths, ideas and research of neuroevolution

Size: 3.91 KB - Last synced at: over 2 years ago - Pushed at: almost 8 years ago - Stars: 1 - Forks: 0

FaydSpeare/neat-v2

Improved version of FaydSpeare/NEAT (Neuroevolution of Augmenting Topologies) with Persistent Innovation Numbers. Includes HyperNEAT package.

Language: Python - Size: 62.5 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0

Liikt/GoNEAT

I need a better brain, so I code one. EDIT: Turns out this brain is even slower than mine

Language: Go - Size: 43.9 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0