gym-simpletetris 0.0.2

A simple Tetris engine for OpenAI Gym

gym-simpletetris

Simple Tetris is a simple Tetris environment built entirely in Python. Several options are provided for modifying the environment and its reward system.

Installation

pip

The preferred installation of gym-simpletetris is via pip:

pip install gym-simpletetris

Clone the project

The code is easy to read and modify. If you wish to modify the package to your needs, then follow these instructions:

1. Fork the project
2. Download it using:

git clone https://github.com/<YOUR-USERNAME>/gym-simpletetris

3. Make your changes
4. Install it using pip:

cd gym-simpletetris
pip install -e ./

Usage

You can create an environment using gym.make and supplying the environment id.

import gym
import gym_simpletetris

env = gym.make('SimpleTetris-v0')
obs = env.reset()

episode = 0
while episode < 10:
    action = env.action_space.sample()
    obs, reward, done, info = env.step(action)
    
    if done:
        print(f"Episode {episode + 1} has finished.")
        episode += 1
        obs = env.reset()

env.close()

Environment

Several options are provided to modify the environment. Arguments can be used at the creation of the environment:

import gym
import gym_simpletetris

env = gym.make('SimpleTetris-v0',
               height=20,                       # Height of Tetris grid
               width=10,                        # Width of Tetris grid
               obs_type='ram',                  # ram | grayscale | rgb
               extend_dims=False,               # Extend grayscale dimensions
               render_mode='rgb_array',         # Only supports rgb_array
               reward_step=False,               # see reward table
               penalise_height=False,           # see reward table
               penalise_height_increase=False,  # see reward table
               advanced_clears=False,           # see reward table
               high_scoring=False               # see reward table
               )

If using an observation type of grayscale or rgb then the environment will be as an array of size 84 x 84. If using grayscale, then the grid can be returned as 84 x 84 or extended to 84 x 84 x 1 if entend_dims is set to True. The rgb array will always be returned as 84 x 84 x 3.

Note: The environment only supports rendering as rgb_array at this time but a human render option is planned in a future update.

Reward Table

Option	Description
reward_step	Adds a reward of +1 for every time step that does not include a line clear or end of game.
penalise_height	Penalises the height of the current Tetris tower at every time step. A negative reward equal to the height of the current tower is added at every time step.
penalise_height_increase	Penalises an increase in the height of the Tetris tower. At each time step, if the height increases then a negative reward equal to the increase is given.
advanced_clears	Changes the rewards for clearing lines to be similar to the modern Tetris system. The new rewards are 100 for a single line clear, 250 for a double line clear, 750 for a triple line clear and 3000 for a Tetris (quadruple line clear).
high_scoring	Changes the reward given for each line clear to 1000.

Note: penalise_height and penalise_height_increase cannot be used together. If both are enabled then penalise_height will be used.

info dictionary

The info dictionary returned by each step includes the following keys:

Key	Type	Description
time	int	The time passed (no. of steps) since the start of the current game
current_piece	string	The letter representing the current piece
score	int	The score of the current game
lines_cleared	int	The number of lines cleared in the current game
statistics	dict	The number of Tetris pieces dispatched by type