There are 0 repository under neuro-evolution topic.
🥕 Evolutionary Neural Networks in JavaScript
🦖 A fast & simple neuro-evolution library for Python
Several approaches using deep reinforcement learning to play Super Mario Bros.
Genetic Algorithm for Neural Network Architecture and Hyperparameter Optimization and Neural Network Weight Optimization with Genetic Algorithm
Genetic algorithm (NEAT) to generate and optimize deep neural networks for the game "Flappy Bird".
Developing an Intelligent Agent from scratch to play a game with Applying Neuroevolution to achieve high scores
Machine learning model that learns to play Flappy bird game developed using Neural networks and Genetic algorithm(NEAT).
I'm learning about machine learning algorithms by implementing them and using them in Java.
neuro-evolution applied to the game of rock paper scissors
Which dynamical regime is beneficial for biological systems in the context of the criticality hypothesis? Agent-based evolutionary foraging game with experiments to evaluate generalizability, ability to perform complex tasks and evolvability of agents with respect to their dynamical regime. Paper: https://arxiv.org/abs/2103.12184
An implementation of the NEAT-Algorithm and an UE4 project to try it out.
Evolução Neural aplicada ao jogo Flappy Bird.
Python implementation of the Semantic Learning Machine
Paper: https://doi.org/10.1162/isal_a_00412 Which dynamical regime is beneficial for biological systems? Agent-based evolutionary foraging game with experiments to evaluate generalizability, ability to perform complex tasks and evolvability.
The project aims to teach a neural net how to play the famous game 'Flappy Bird'. To play the game deep learning and genetic algorithms are applied.
A flexible NEAT-based neural network library for .NET, empowering intelligent agents in research, games, and AI simulations.
This is a neuro-evolution of augmenting topologies library. It uses a genetic algorithm to evolve neural networks. This is useful when you don't have a dataset to train your neural network, for example when you need an agent to interact with an environment or to learn to play some games.
Various studies show that criticality is an attractor in biological evolution. Which conditions have to be fulfilled, such that criticality acts as an attractor in our neuroevolution simulation? -- Masters Thesis Project ---
Implemented Multilayer Perceptron (MLP) and Radial Basis Function (RBF) neural networks from scratch in Python and used ResNet-34 as a feature extractor. Evaluated and compared the classification accuracy of the two networks on the CIFAR-10 dataset.
Implemented an intelligent game agent using an evolutionary algorithm to train a neural network.
Not the typical snake game. The snake no longer needs you - it grows on its own (neuro-evolution at its best)
contains code related to all machine learning models being studied.
Neuroevolution through Augmenting Topologies
The power of Neural Networks and neuro-evolution. Creating and training digital creatures to find the path to a target.
Hyper-Parameter Optimisation experiment as part of my undergraduate dissertation (2019)