gym-tetris 2.0.2

Tetris (NES) for OpenAI Gym

gym-tetris

An OpenAI Gym environment for Tetris on The Nintendo Entertainment System (NES) based on the nes-py emulator.

Installation

The preferred installation of gym-tetris is from pip:

pip install gym-tetris

Usage

Python

You must import gym_tetris before trying to make an environment. This is because gym environments are registered at runtime. By default, gym_tetris environments use the full NES action space of 256 discrete actions. To constrain this, gym_tetris.actions provides an action list called MOVEMENT (20 discrete actions) for the nes_py.wrappers.BinarySpaceToDiscreteSpaceEnv wrapper.

from nes_py.wrappers import BinarySpaceToDiscreteSpaceEnv
import gym_tetris
from gym_tetris.actions import MOVEMENT

env = gym_tetris.make('Tetris-v0')
env = BinarySpaceToDiscreteSpaceEnv(env, MOVEMENT)

done = True
for step in range(5000):
    if done:
        state = env.reset()
    state, reward, done, info = env.step(env.action_space.sample())
    env.render()

env.close()

NOTE: gym_tetris.make is just an alias to gym.make for convenience.

NOTE: remove calls to render in training code for a nontrivial speedup.

Command Line

gym_tetris features a command line interface for playing environments using either the keyboard, or uniform random movement.

gym_tetris -m <`human` or `random`>

Step

Info about the rewards and info returned by the step method.

Reward Function

The reward function assumes the objective of the game is to increase the score. As such, the reward is defined as the instantaneous change in score for a given action.

info dictionary

The info dictionary returned by the step method contains the following keys:

Key	Type	Description
current_piece	str	the current piece as a string
number_of_lines	int	the number of cleared lines
score	int	the current score of the game
next_piece	str	the next piece on deck
statistics	dict	statistics for each piece

Citation

Please cite gym-tetris if you use it in your research.

@misc{gym-tetris,
  author = {Christian Kauten},
  title = {{Tetris (NES)} for {OpenAI Gym}},
  year = {2019},
  publisher = {GitHub},
  howpublished = {\url{https://github.com/Kautenja/gym-tetris}},
}

References

The following references contributed to the construction of this project.

1. Tetris (NES): RAM Map. Data Crystal ROM Hacking.
2. Tetris: Memory Addresses. NES Hacker.
3. Applying Artificial Intelligence to Nintendo Tetris. MeatFighter.