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novelty-search

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This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima

  • Updated Jul 30, 2024
  • Go

GAGA is a fast, header only, multi-objective, and distributed evolutionary algorithm library written in modern C++. It is designed to be easily usable with various genotype representations and allows the user to enable or disable several features such as novelty search or speciation. It also produces and exports various customizable statistics.

  • Updated Oct 6, 2021
  • C++

A universal supervisor controller and ER suite for Webots that can be adapted to any wheeled robot morphology with ease. The project is also setup to allow for easy Reinforcement Learning experimentation with some select algorithms (CMA-ES, Novlty Search, MAP-Elites) and neural networks (fixed and recurrent).

  • Updated Apr 4, 2021
  • Python

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