https://github.com/ram81/flappybot

Implementation of Flappy Bird Bot using Neural Network and Genetic Algorithm
https://github.com/ram81/flappybot

Last synced: 7 days ago
JSON representation

Implementation of Flappy Bird Bot using Neural Network and Genetic Algorithm

• Host: GitHub
• URL: https://github.com/ram81/flappybot
• Owner: Ram81
• Created: 2017-09-10T11:44:37.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2018-11-04T12:11:33.000Z (over 6 years ago)
• Last Synced: 2025-02-25T04:44:06.301Z (4 months ago)
• Language: JavaScript
• Homepage:
• Size: 2.7 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

        
# Implementation of Flappy Bird Bot using Neural Network and Genetic Algorithm.

Here is the source code for a HTML5 project that implements a machine learning algorithm in the Flappy Bird video game using neural networks and a genetic algorithm. The program teaches a little bird how to flap optimally in order to fly safely through barriers as long as possible.

All code is written in HTML5 using [Phaser framework](http://phaser.io/) and [Synaptic Neural Network library](https://synaptic.juancazala.com) for neural network implementation.

![Flappy Bird Screenshot](https://raw.githubusercontent.com/ram81/FlappyBot/master/screenshots/flappy_10.png "Flappy Bird Screenshot")

## Neural Network Architecture

To play the game, each unit (bird) has its own neural network consisted of the next 3 layers:

1. an input layer with 2 neurons presenting what a bird sees:

     

     ```

     1) horizontal distance between the bird and the closest gap

     2) height difference between the bird and the closest gap

     ```

     

2. a hidden layer with 6 neurons

3. an output layer with 1 neuron used to provide an action as follows:

     

     ```

    if output > 0.5 then flap else do nothing

     ```

     

![Flappy Bird Neural Network](https://raw.githubusercontent.com/ram81/FlappyBot/master/screenshots/flappy_06.png "Flappy Bird Neural Network")

There is used [Synaptic Neural Network library](https://synaptic.juancazala.com) to implement entire artificial neural network instead of making a new one from the scratch.

## The Main Concept of Machine Learning

The main concept of machine learning implemented in this program is based on the neuro-evolution form. It uses evolutionary algorithms such as a genetic algorithm to train artificial neural networks. Here are the main steps:

1. create a new population of 10 units (birds) with a **random neural network** 

2. let all units play the game simultaneously by using their own neural networks

3. for each unit calculate its **fitness** function to measure its quality as:

    ```

    fitness = total travelled distance - distance to the closest gap

    ```

 

    ![Flappy Bird Fitness](https://raw.githubusercontent.com/ram81/FlappyBot/master/screenshots/flappy_08.png "Flappy Bird Fitness")

    

4. when all units are killed, evaluate the current population to the next one using **genetic algorithm operators** (selection, crossover and mutation) as follows:

    ```

    1. sort the units of the current population in decreasing order by their fitness ranking

    2. select the top 4 units and mark them as the winners of the current population

    3. the 4 winners are directly passed on to the next population

    4. to fill the rest of the next population, create 6 offsprings as follows:

        - 1 offspring is made by a crossover of two best winners

        - 3 offsprings are made by a crossover of two random winners

        - 2 offsprings are direct copy of two random winners

    5. to add some variations, apply random mutations on each offspring.

    ```

    

5. go back to the step 2

## Implementation

### Requirements

Since the program is written in HTML5 using [Phaser framework](http://phaser.io/) and [Synaptic Neural Network library](https://synaptic.juancazala.com) you need these files:

- **phaser.min.js**

- **synaptic.min.js**

### NOTE 

The implementation is currently supported only on Firefox. The project is based on the repository [here](https://github.com/ssusnic/Machine-Learning-Flappy-Bird).