gym-simpletetris 0.4.0

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 ram or grayscale dimensions
               render_mode='rgb_array',         # Unused parameter
               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
               penalise_holes=False,            # See reward table
               penalise_holes_increase=False,   # See reward table
               lock_delay=0,                    # Lock delay as number of steps
               step_reset=False                 # Reset lock delay on step downwards
               )

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. If using an observation type of ram and extend_dims is set then an array of size width x height x 1 is returned.

Note: The default render mode is human. The render_mode parameter does not alter the default render mode. To render using rgb_array then please use the mode option when calling env.render(mode='rgb_array').

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.
penalise_holes	Penalises the number of holes in the current Tetris tower. A hole is an empty cell with at least one non-empty cell above it.
penalise_holes_increase	Penalises an increase in the number of holes in the current Tetris tower.

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

Note: penalise_holes and penalise_holes_increase cannot be used together. If both are enabled then penalise_holes 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
holes	int	The number of holes in the current Tetris tower
deaths	int	The number of deaths since the environment was created
statistics	dict	The number of Tetris pieces dispatched by type