Metadata-Version: 2.1
Name: rlgym
Version: 0.2.0
Summary: A python API that can be used to treat the game Rocket League as an Openai Gym-like environment for Reinforcement Learning projects.
Home-page: https://github.com/lucas-emery/rocket-league-gym
Author: Lucas Emery and Matthew Allen
License: Apache 2.0
Description: # The Rocket League Gym
        This is a python API that can be used to treat the game [Rocket League](https://www.rocketleague.com) as though it were an [Openai Gym](https://gym.openai.com)-style environment for Reinforcement Learning projects. This API must be used with the accompanying Bakkesmod plugin.
        
        ## Requirements
        * A Windows 10 PC
        * The Steam version of Rocket League (Epic version might be supported but hasn't been tested)
        * [Bakkesmod](https://www.bakkesmod.com)
        * The RLGym plugin for Bakkesmod (It's installed automatically by pip)
        * Python >= 3.7
        
        ## Installation
        Install the library via pip:
        ```
        pip3 install rlgym
        ```
        Then simply run ```example.py``` from our repo to ensure everything works.
        
        ## Usage
        To run a premade environment, call ```rlgym.make``` with the name of the environment you would like to create.
        For example, the following code will create an instance of the Duels environment:
        ```python
        import rlgym
        env = rlgym.make("Duel")
        ```
        If you would like to build any environment with self-play enabled, include the keyword "self" (not case sensitive) in the name of the environment, like so:
        ```python
        import rlgym
        env = rlgym.make("DuelSelf")
        ```
        You can take a look at `example_self.py` to see how to handle observations and actions when dealing with more than one agent.
        
        ---
        RLGym comes with 3 pre-made environments:
        * Duel
        * Doubles
        * Standard
        
        Each can be instantiated by calling ```rlgym.make``` with the name of the environment you would like to create. 
        
        RLGym also provides you the ability to create your own environments with a number of potential configurations through optional parameters: 
        ```python
        env = rlgym.make("Duel", 
                         ep_len_minutes: float,
                         game_speed: int,
                         tick_skip: int,
                         spawn_opponents: bool,
                         random_resets: bool,
                         team_size: int,
                         terminal_conditions: List[rlgym.utils.TerminalCondition],
                         reward_fn: rlgym.utils.RewardFunction,
                         obs_builder: rlgym.utils.ObsBuilder)
        ```
        For more information on how to build a custom RLGym environment, please visit our Wiki.
        
Keywords: rocket-league,gym,reinforcement-learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: Microsoft :: Windows
Requires-Python: >=3.7
Description-Content-Type: text/markdown
