Metadata-Version: 1.0
Name: gym_gridworlds
Version: 0.0.2
Summary: Gridworlds environments for OpenAI gym.
Home-page: https://github.com/podondra/gym-gridworlds
Author: Ondřej Podsztavek
Author-email: ondrej.podsztavek@gmail.com
License: MIT License
Description-Content-Type: UNKNOWN
Description: OpenAI gym Gridworlds
        =====================
        
        Implementation of three gridworlds environments
        from book `Reinforcement Learning: An Introduction
        <http://incompleteideas.net/book/the-book-2nd.html>`_
        compatible with `OpenAI gym <https://github.com/openai/gym>`_.
        
        Usage
        -----
        
        .. code::
        
                $ import gym
                $ import gym_gridworlds
                $ env = gym.make('Gridworld-v0')  # substitute environment's name
        
        ``Gridworld-v0``
        ----------------
        
        Gridworld is simple 4 times 4 gridworld from example 4.1 in the [book].
        There are fout action in each state (up, down, right, left)
        which deterministically cause the corresponding state transitions
        but actions that would take an agent of the grid leave a state unchanged.
        The reward is -1 for all tranistion until the terminal state is reached.
        The terminal state is in top left and bottom right coners.
        
        ``WindyGridworld-v0``
        ---------------------
        
        Windy gridworld is from example 6.5 in the book_.
        Windy gridworld is a standard gridworld as described above
        but there is a crosswind upward through the middle of the grid.
        Action are standard but in the middle region the resultant states are
        shifted upward by a wind which strength varies between columns.
        
        .. _book: http://incompleteideas.net/book/the-book-2nd.html
        
        ``Cliff-v0``
        ------------
        
        Cliff walking is a gridworld example 6.6 from the book_.
        Again reward is -1 on all transition except those into region
        that is cliff.
        Stepping into this region incurs a reward of -100
        and sends the agent instantly back to the start.
        
Platform: UNKNOWN
