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        "description": "# Seoul AI Gym\n\n**Seoul AI Gym is a toolkit for developing AI algorithms.**\nThis `gym` simulates environments and enables you to apply any teaching technique on agent.\n\n[![Build Status](https://api.travis-ci.com/seoulai/gym.svg?branch=master)](https://travis-ci.com/seoulai/gym)\n\nSeoul AI Gym was inspired by [OpenAI gym](https://github.com/openai/gym) and tries to follow its API very closely.\n\n\n### Contents\n* [Basics](https://github.com/seoulai/gym#basics)\n* [Installation](https://github.com/seoulai/gym#installation)\n  * [`pip3`](https://github.com/seoulai/gym#pip3)\n  * [From source](https://github.com/seoulai/gym#from-source)\n* [Environments](https://github.com/seoulai/gym#environments)\n* [Examples](https://github.com/seoulai/gym#examples)\n* [Testing](https://github.com/seoulai/gym#testing)\n\n## Basics\nThere are two terms that are important to understand: *Environment* and *Agent*.\n\nAn environment is a world (simulation) with which an agent can interact.\nAn agent can observe a world and act based on its decision.\n\n`seoulai-gym` provides environments.\nAn example of creating environment:\n\n```python\nimport seoulai_gym as gym\nenv = gym.make(\"Checkers\")\n```\n\nEvery environment has three important methods: `reset`, `step` and `render`.\n\n##### `reset(self) -> observation`\nReset an environment to default state and return `observation` of default state.\n`observation` data structure depends on environment and is described separately for each environment.\n\n##### `step(self, agent, action) -> observation, reward, done, info`\nPerform an `action` on behalf of `agent` in environment lastly observed by either `reset` or `step`.\nAn `action` can differ among different environments but the return value of `step` method is always same.\nA `reward` is given to an agent when action that was done in the current step or some of the previous steps have led to a positive outcome for an agent (e.g winning a game).\nAn `info` is a dictionary containing extra information about performed `action`.\n\n##### `render(self) -> None`\nDisplay state of game on a screen.\n\n\n## Installation\nThere are two ways to install `seoulai-gym`.\n\n#### `pip3`\nThe recommended way for developers creating an agent is to install `seoulai-gym` using `pip3`.\n```\npip3 install seoulai-gym\n```\n\n#### From source\nYou can also clone and install `seoulai-gym` from source.\nThis option is for developers that want to create new environments or modify existing ones.\n\n```shell\ngit clone https://github.com/seoulai/gym.git\ncd gym\npip3 install -e .\n```\n\n#### Supported systems\n`seoulai-gym` requires to have at least Python 3.6 and was tested on Arch Linux, macOS High Sierra and Windows 10.\n\n## Environments\nCurrently, environment simulating game of [Checkers](https://en.wikipedia.org/wiki/Draughts), [Mighty] (https://en.wikipedia.org/wiki/Mighty_(card_game)), and Market are provided.\n\n* Checkers\n  ```python\n  import seoulai_gym as gym\n  env = gym.make(\"Checkers\")\n  env.reset()\n  env.render()\n  ```\n\n* Mighty\n  ```python\n  import seoulai_gym as gym\n  from seoulai_gym.envs.mighty.agent.RandomAgent import RandomAgent\n\n  env = gym.make(\"Mighty\")\n  players = [RandomAgent(\"Agent 1\", 0),\n              RandomAgent(\"Agent 2\", 1),\n              RandomAgent(\"Agent 3\", 2),\n              RandomAgent(\"Agent 4\", 3),\n              RandomAgent(\"Agent 5\", 4)]\n  obs = env.reset()\n  obs[\"game\"].players = [\n    players[0]._name,\n    players[1]._name,\n    players[2]._name,\n    players[3]._name,\n    players[4]._name,\n    ]\n  env.render()\n\n* Market\n\n  ```python\n  import seoulai_gym as gym\n  from seoulai_gym.envs.traders.agents import RandomAgentBuffett\n\n  # make enviroment\n  env = gym.make(\"Market\")\n\n  # select exchange\n  env.select(\"upbit\")\n\n  init_cash = 100000000  # KRW\n  a1 = RandomAgentBuffett(\"Buffett\", init_cash)\n  current_agent = a1\n\n  env.reset()\n  env.render()\n  ```\n\n## Examples\n\n* Checkers\n  * https://github.com/seoulai/gym/blob/master/examples/checkers_example.py\n\n    [![Watch the video](https://i.ytimg.com/vi/O-Q9hg7Vng8/hqdefault.jpg)](https://youtu.be/O-Q9hg7Vng8)\n\n* Mighty\n  * https://github.com/seoulai/gym/blob/master/examples/mighty_example.py\n\n    [![Watch the video](http://img.youtube.com/vi/M3GCt8evGkQ/0.jpg)](https://youtu.be/M3GCt8evGkQ?t=0s)\n\n* Market\n  * https://github.com/seoulai/gym/blob/master/examples/trader_example.py\n\n\n## Testing\nAll test are written using [pytest](http://doc.pytest.org/).\nYou can run them via:\n\n```\npytest\n```\n\n\n",
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