Metadata-Version: 1.1
Name: gym_ple
Version: 0.3
Summary: This package allows to use PLE as a gym environment.
Home-page: https://github.com/lusob/gym-ple
Author: lusob
Author-email: luis@sobrecueva.com
License: UNKNOWN
Description: gym-ple
        ******
        
        PyGame Learning Environment (PLE) is a learning environment, mimicking the Arcade Learning Environment interface, allowing a quick start to Reinforcement Learning in Python. 
        The goal of PLE is allow practitioners to focus design of models and experiments instead of environment design.
        This package allows to use PLE as a gym environment.
        
        Installing everything
        ---------------------
        gym_ple requires PLE, to install PLE clone the repo and install with pip.
        
        .. code:: shell
        
            git clone https://github.com/ntasfi/PyGame-Learning-Environment.git
            cd PyGame-Learning-Environment/
            pip install -e .
        
        
        PLE requires PyGame installed:
        
        On OSX:
        
        .. code:: shell
        
            brew install sdl sdl_ttf sdl_image sdl_mixer portmidi  # brew or use equivalent means
            conda install -c tlatorre pygame=1.9.2 # using Anaconda
        
        On Ubuntu 14.04:
        
        .. code:: shell
        
            apt-get install -y python-pygame
        
        More configurations and installation details on: http://www.pygame.org/wiki/GettingStarted#Pygame%20Installation
        
        And finally clone and install this package
        
        .. code:: shell
        
            git clone https://github.com/lusob/gym-ple.git 
            cd gym-ple/
            pip install -e .
        
        You also can install it from PyPi:
        
        .. code:: shell
        
            pip install gym_ple 
        
        
        Example
        =======
        
        Run ``python example.py`` file to play a PLE game (flappybird) with a random_agent (you need to have installed openai gym).
        
        
Keywords: AI,Reinforcement Learning,Games
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
