Flappy Bird for Gymnasium

This repository contains the implementation of Gymnasium environment for the Flappy Bird game. The implementation of the game's logic and graphics was based on the flappy-bird-gym project, by @Talendar.

State space

The "FlappyBird-v0" environment, yields simple numerical information about the game's state as observations representing the game's screen.

FlappyBird-v0

There exist two options for the observations:

1. option

• The LIDAR sensor 180 readings (Paper: Playing Flappy Bird Based on Motion Recognition Using a Transformer Model and LIDAR Sensor)

2. option

• the last pipe's horizontal position
• the last top pipe's vertical position
• the last bottom pipe's vertical position
• the next pipe's horizontal position
• the next top pipe's vertical position
• the next bottom pipe's vertical position
• the next next pipe's horizontal position
• the next next top pipe's vertical position
• the next next bottom pipe's vertical position
• player's vertical position
• player's vertical velocity
• player's rotation

Action space

• 0 - do nothing
• 1 - flap

Rewards

• +0.1 - every frame it stays alive
• +1.0 - successfully passing a pipe
• -1.0 - dying
• −0.5 - touch the top of the screen

Installation

To install flappy-bird-gymnasium, simply run the following command:

$ pip install flappy-bird-gymnasium

Usage

Like with other gymnasium environments, it's very easy to use flappy-bird-gymnasium. Simply import the package and create the environment with the make function. Take a look at the sample code below:

import flappy_bird_gymnasium
import gymnasium
env = gymnasium.make("FlappyBird-v0", render_mode="human", use_lidar=True)

obs, _ = env.reset()
while True:
    # Next action:
    # (feed the observation to your agent here)
    action = env.action_space.sample()

    # Processing:
    obs, reward, terminated, _, info = env.step(action)
    
    # Checking if the player is still alive
    if terminated:
        break

env.close()

Playing

To play the game (human mode), run the following command:

$ flappy_bird_gymnasium

To see a random agent playing, add an argument to the command:

$ flappy_bird_gymnasium --mode random

To see a Deep Q Network agent playing, add an argument to the command:

$ flappy_bird_gymnasium --mode dqn