Welcome to lunarlander_gym's documentation!
===========================================

Summary
-------

This project is implementation of multiple AI agents based on different
Reinforcement Learning methods to OpenAI Gymnasium Lunar-Lander
environment which is classic rocket landing trajectory optimization
problem.

-  Free software: MIT license
-  Home Page:
   `https://github.com/Ehsan2754/lunarlander_gym <https://github.com/Ehsan2754/lunarlander_gym>`__.


Evaluation
===========

+-------------+-------------+-------------+-------------+-------------+
|             | RandomAgent | Gradient    | Q-Learning  | A           |
|             |             | Policy      | Agent       | ctor-critic |
|             |             | Agent       |             | Agent       |
+=============+=============+=============+=============+=============+
| Training    | 0           | 10,000      | 3000        | 3000        |
| episodes    |             |             |             |             |
+-------------+-------------+-------------+-------------+-------------+
| Reward      | -70.46      | 49.07       | 198.51      | 284.86      |
+-------------+-------------+-------------+-------------+-------------+





.. toctree::
   :maxdepth: 2
   :caption: Contents:

   readme
   installation
   usage
   modules
   contributing
   authors
   history

Indices and tables
==================
* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`