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An OpenAI Gym environment for Chrome Dino / T-Rex Runner Game

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gym-chrome-dino

An OpenAI Gym environment for Chrome Dino / T-Rex Runner Game

screenshot

This environment utilizes a forked version of Chrome Dino, also called T-Rex Runner, extracted from chromium offline error page. See here.

Installation

You can install gym-chrome-dino from PyPI by either

pip install gym-chrome-dino

or

git clone https://github.com/elvisyjlin/gym-chrome-dino.git
cd gym-chrome-dino
pip install -e .

Usage

You can get started as follows:

import gym
import gym_chrome_dino
env = gym.make('ChromeDino-v0')

To create a headless (without opening browser) environment

env = gym.make('ChromeDinoNoBrowser-v0')

Observations, Actions and Rewards

  • The observation is a RGB numpy array with shape of (150, 600, 3).
  • The available actions are 0: do nothing, 1: jump, and 2: duck.
  • A positive reward 0.01 is given when the dinosaur is alive; a negative penalty -1.0 is given when the dinosaur hits an obstable, which might be a cactus or a bird.

For the DeepMind DQN recipe, where we give 4-stacked resized grayscaled frames (80, 160, 4) to the agent, we provide a wrapping method make_dino(). It also comes with a timer wrapper, which reports the interval between env.step().

from gym_chrome_dino.wrappers import make_dino
env = make_dino(env, timer=True, frame_stack=True)

DinoGame

An instance of DinoGame is created when the environment is made. There are some useful methods for fine control of the training environment. The DineGame can be accessed as follows:

env.unwrapped.game

DinoGame provides a get_score() method to get the score of current game.

score = env.unwrapped.game.get_score()

By default, the acceleration of the game is set to zero. If you want to restore the original acceleration value, please do set_acceleration(True). On the other hand, set_acceleration(False) sets the value to zero.

env.unwrapped.game.set_acceleration(True)

Example

Here is a simple example to use gym-chrome-dino.

import gym
import gym_chrome_dino
from gym_chrome_dino.utils.wrappers import make_dino
env = gym.make('ChromeDino-v0')
env = make_dino(env, timer=True, frame_stack=True)
done = True
while True:
    if done:
        env.reset()
    action = env.action_space.sample()
    observation, reward, done, info = env.step(action)

WebDriver

gym-chrome-dino runs the game on chromedriver via selenium because it is a proper way to monitor and to play Chrome Dino. As a result, the latest chromedriver executable file will be downloaded to the current working directory where your program is.

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An OpenAI Gym environment for Chrome Dino / T-Rex Runner Game

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