Flappy-AI is a project that utilizes the NEAT (NeuroEvolution of Augmenting Topologies) algorithm to create an AI that learns to play the game Flappy Bird. The repository includes all necessary assets, configuration files, and code to run the project.

A Python program to play the first or second level of Donkey Kong Country (SNES, 1996), Jungle Hijinks or Ropey Rampage, using the genetic algorithm NEAT (NeuroEvolution of Augmenting Topologies) and Gymnasium, a maintained fork of OpenAI's Gym.

Flappy Bird Game with AI

Integrates the classic Pong game with AI using NEAT (NeuroEvolution of Augmenting Topologies) to train neural networks through evolutionary principles. Watch as the AI evolves to master Pong by competing and improving over generations.

Use of machine learning to make a car complete a circuit (not great, but it was for kids)

Implementacion of NEAT algorithm, PPO algorithm and Genetic algorithm to train agents in the game Airstriker-Genesis, using gym-retro environment.

The project showcases the implementation of the NEAT algorithm in Python to play a Flappy Bird-like game. It orchestrates the evolution and evaluation of a bird population through successive generations until the fitness threshold is met. The ultimate winner genome, demonstrating exceptional gameplay, is saved as a pickle file as the main output.

Using Python and the NEAT genetic algorithm to grow neural cellular automata patterns

FlappyBirdAI utilizes NEAT Python to train an AI to master Flappy Bird. Employing genetic algorithms, this project evolves neural networks over generations to improve gameplay performance automatically. Ideal for developers and AI enthusiasts exploring game AI and evolutionary algorithms in Python.

This project demonstrates training an AI to play a Pong game (developed using pygame) using the NEAT (NeuroEvolution of Augmenting Topologies) algorithm.

Biologically Inspired rtNEAT

An implementation of Flappy Bird by Dong Nguyen (2013) in Python, as well as a NEAT (NeuroEvolution of Augmenting Topologies) genetic algorithm to learn and play the game.

Using Neural Networks through the NEAT algorithm for the birds so they can learn how to play Flappy Bird

sNEAT: A simplified implementation of NEAT (Neuro-Evolution of Augmenting Topologies) in Python

Python application that finds a path between two points with the help of deep learning. The application is devoloped for my graduation projects needs.

This will utilize neural network and machine learning models to paper trade on the stock market.

An attempt at making an AI learn to play the game Celeste using Neuroevolution of Augmenting Topologies (NEAT), specifically neat-python.

FlappyAI is our exploration of the NeuroEvolution of Augmenting Topologies (NEAT) algorithm. Using this algorithm, we built the Flappy Bird game with Pygame and trained a neural network to play the game autonomously. This project showcases NEAT's capability in creating adaptive and intelligent game-playing systems.

The classic Flappy Bird game recreated in Python and Pygame and integrated with NEAT

Auto-Flappy: An AI-driven adaptation of Flappy Bird, trained using NEAT, offering autonomous gameplay.