Not the typical snake game. The snake no longer needs you - it grows on its own (neuro-evolution at its best)
-
Updated
Sep 16, 2023 - Python
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
Hyper-Parameter Optimisation experiment as part of my undergraduate dissertation (2019)
The power of Neural Networks and neuro-evolution. Creating and training digital creatures to find the path to a target.
"Neuro Evolution of Augmenting Topologies"
A flexible NEAT-based neural network library for .NET, empowering intelligent agents in research, games, and AI simulations.
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.
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.
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 an intelligent game agent using an evolutionary algorithm to train a neural network.
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.
Heuristic AI for playing Tetris. Uses neuro-evolution algorithm.
Python implementation of the Semantic Learning Machine
Evolução Neural aplicada ao jogo Flappy Bird.
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.
An implementation of the NEAT-Algorithm and an UE4 project to try it out.
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
neuro-evolution applied to the game of rock paper scissors
I'm learning about machine learning algorithms by implementing them and using them in Java.
Add a description, image, and links to the neuro-evolution topic page so that developers can more easily learn about it.
To associate your repository with the neuro-evolution topic, visit your repo's landing page and select "manage topics."