There are 19 repositories under genetic-algorithms topic.
Machine Learning for Flappy Bird using Neural Network and Genetic Algorithm
GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs).
source code from the book Genetic Algorithms with Python by Clinton Sheppard
Using artificial intelligence and genetic algorithms to automatically write programs. Tutorial: http://www.primaryobjects.com/cms/article149
Evolving version of Conway’s Game of Life.
[CCF-A] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based randomized optimizers, pattern search, and even random search). [https://jmlr.org/papers/v25/23-0386.html] (Its Planned Extensions: PyCoPop7, PyNoPop7, PyPop77, and PyMePop7)
A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)
Source Code for the Book Classic Computer Science Problems in Swift
A pytorch implementation of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm
This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).
Twitter Genetic Algorithm Imagery
EC-KitY: A scikit-learn-compatible Python tool kit for doing evolutionary computation.
Hyperparameter tuning for machine learning models using a distributed genetic algorithm
Python implementation for TSP using Genetic Algorithms, Simulated Annealing, PSO (Particle Swarm Optimization), Dynamic Programming, Brute Force, Greedy and Divide and Conquer
Evolve complex cellular automata with a genetic algorithm.
TetNet is an application that uses genetic algorithms to create an evolving Tetris AI.
A Blazor web app developed to explore the use of Genetic Algorithms for solving problems.
Evolutionary Algorithm for the 2D Packing Problem combined with the 0/1 Knapsack Problem (Master Thesis)
Heuristic global optimization algorithms in Python
🧬 Modularised Evolutionary Algorithms For Python with Optional JIT and Multiprocessing (Ray) support. Inspired by PyTorch Lightning
EasyGA is a python package designed to provide an easy-to-use Genetic Algorithm. The package is designed to work right out of the box, while also allowing the user to customize features as they see fit.
"Using Genetic Algorithms for Multi-depot Vehicle Routing" paper implementation.
Biologically-Inspired and Machine Learning Algorithms written in Python
Implementation of Mind Evolution, Evolving Deeper LLM Thinking, from Deepmind
Supported highly optimized and flexible genetic algorithm package for python3.8+
🐤The next evolution of evolution.
Usage of genetic algorithms to train a neural network in multiple OpenAI gym environments.
Exploration into the Firefly algorithm in Pytorch
An automated time table generator using genetic algorithms in java.
Making a Class Schedule Using a Genetic Algorithm