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        "author": "Christian Kauten",
        "author_email": "kautencreations@gmail.com",
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        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: Free For Educational Use",
            "Operating System :: MacOS :: MacOS X",
            "Operating System :: Microsoft :: Windows",
            "Operating System :: POSIX :: Linux",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Games/Entertainment :: Side-Scrolling/Arcade Games",
            "Topic :: Scientific/Engineering :: Artificial Intelligence"
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        "description": "# gym-tetris\n\n[![BuildStatus][build-status]][ci-server]\n[![PackageVersion][pypi-version]][pypi-home]\n[![PythonVersion][python-version]][python-home]\n[![Stable][pypi-status]][pypi-home]\n[![Format][pypi-format]][pypi-home]\n[![License][pypi-license]](LICENSE)\n\n[build-status]: https://travis-ci.com/Kautenja/gym-tetris.svg?branch=master\n[ci-server]: https://travis-ci.com/Kautenja/gym-tetris\n[pypi-version]: https://badge.fury.io/py/gym-tetris.svg\n[pypi-license]: https://img.shields.io/pypi/l/gym-tetris.svg\n[pypi-status]: https://img.shields.io/pypi/status/gym-tetris.svg\n[pypi-format]: https://img.shields.io/pypi/format/gym-tetris.svg\n[pypi-home]: https://badge.fury.io/py/gym-tetris\n[python-version]: https://img.shields.io/pypi/pyversions/gym-tetris.svg\n[python-home]: https://python.org\n\n<p align=\"center\">\n<img\n  src=\"https://user-images.githubusercontent.com/2184469/58226585-ee152500-7cec-11e9-84a9-1658e4012361.jpg\"\n  height=\"300px\" />\n<img\n  src=\"https://user-images.githubusercontent.com/2184469/58226782-cffbf480-7ced-11e9-8f55-a42baae35fbd.png\"\n  width=\"320px\" />\n</p>\n\nAn [OpenAI Gym](https://github.com/openai/gym) environment for Tetris on The\nNintendo Entertainment System (NES) based on the\n[nes-py](https://github.com/Kautenja/nes-py) emulator.\n\n## Installation\n\nThe preferred installation of `gym-tetris` is from `pip`:\n\n```shell\npip install gym-tetris\n```\n\n## Usage\n\n### Python\n\nYou must import `gym_tetris` before trying to make an environment.\nThis is because gym environments are registered at runtime. By default,\n`gym_tetris` environments use the full NES action space of 256\ndiscrete actions. To constrain this, `gym_tetris.actions` provides\nan action list called `MOVEMENT` (20 discrete actions) for the\n`nes_py.wrappers.JoypadSpace` wrapper. There is also\n`SIMPLE_MOVEMENT` with a reduced action space (6 actions). For exact details,\nsee [gym_tetris/actions.py](gym_tetris/actions.py).\n\n```python\nfrom nes_py.wrappers import JoypadSpace\nimport gym_tetris\nfrom gym_tetris.actions import MOVEMENT\n\nenv = gym_tetris.make('Tetris-v0')\nenv = JoypadSpace(env, MOVEMENT)\n\ndone = True\nfor step in range(5000):\n    if done:\n        state = env.reset()\n    state, reward, done, info = env.step(env.action_space.sample())\n    env.render()\n\nenv.close()\n```\n\n**NOTE:** `gym_tetris.make` is just an alias to `gym.make` for\nconvenience.\n\n**NOTE:** remove calls to `render` in training code for a nontrivial\nspeedup.\n\n### Command Line\n\n`gym_tetris` features a command line interface for playing\nenvironments using either the keyboard, or uniform random movement.\n\n```shell\ngym_tetris -e <environment ID> -m <`human` or `random`>\n```\n\n## Environments\n\nThere are two game modes define in NES Tetris, namely, A-type and B-type.\nA-type is the standard endurance Tetris game and B-type is an arcade style mode\nwhere the agent must clear a certain number of lines to win. There are three\npotential reward streams: (1) the change in score, (2) the change in number of\nlines cleared, and (3) a penalty for an increase in board height. The table\nbelow defines the available environments in terms of the game mode (i.e.,\nA-type or B-type) and the rewards applied.\n\n| Environment  | Game Mode | reward score | reward lines | penalize height |\n|:-------------|:----------|:-------------|:-------------|:----------------|\n| `TetrisA-v0` | A-type    | &#9989;      | &#10005;     | &#10005;        |\n| `TetrisA-v1` | A-type    | &#10005;     | &#9989;      | &#10005;        |\n| `TetrisA-v2` | A-type    | &#9989;      | &#10005;     | &#9989;         |\n| `TetrisA-v3` | A-type    | &#10005;     | &#9989;      | &#9989;         |\n| `TetrisB-v0` | B-type    | &#9989;      | &#10005;     | &#10005;        |\n| `TetrisB-v1` | B-type    | &#10005;     | &#9989;      | &#10005;        |\n| `TetrisB-v2` | B-type    | &#9989;      | &#10005;     | &#9989;         |\n| `TetrisB-v3` | B-type    | &#10005;     | &#9989;      | &#9989;         |\n\n## `info` dictionary\n\nThe `info` dictionary returned by the `step` method contains the following\nkeys:\n\n| Key               | Type    | Description\n|:------------------|:--------|:---------------------------------------------|\n| `current_piece`   | `str`   | the current piece as a string\n| `number_of_lines` | `int`   | the number of cleared lines\n| `score`           | `int`   | the current score of the game\n| `next_piece`      | `str`   | the next piece on deck\n| `statistics`      | `dict`  | statistics for each piece\n\n## Citation\n\nPlease cite `gym-tetris` if you use it in your research.\n\n```tex\n@misc{gym-tetris,\n  author = {Christian Kauten},\n  title = {{Tetris (NES)} for {OpenAI Gym}},\n  year = {2019},\n  publisher = {GitHub},\n  howpublished = {\\url{https://github.com/Kautenja/gym-tetris}},\n}\n```\n\n## References\n\nThe following references contributed to the construction of this project.\n\n1. [Tetris (NES): RAM Map](https://datacrystal.romhacking.net/wiki/Tetris_(NES)). _Data Crystal ROM Hacking_.\n2. [Tetris: Memory Addresses](http://www.thealmightyguru.com/Games/Hacking/Wiki/index.php?title=Tetris#Memory_Addresses). _NES Hacker._\n3. [Applying Artificial Intelligence to Nintendo Tetris](https://meatfighter.com/nintendotetrisai/). _MeatFighter._\n\n\n",
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