rllib_local_test_bash.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# **Jupyter Notebook to test the library RLlib in the Gym-Environment JuPong2D**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Checking current directory, it should be the GitLab-Repository\n",
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Activating the virtal environment, which should be installed before running the notebook\n",
    "source lib/pong_deeprl/bin/activate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lists all possible command options of the RLlib training and testing script\n",
    "deep_rllib --help"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Starts a simple training of the Gym-Environment JuPong2D\n",
    "deep_rllib --restore --pl 0.5 --session 1 --stop-iters 10 --checkpoint-freq 5 --num-workers 3 results/rllib_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Testing of the trained model by playing in different Gym-Environments, which depend on the parameters\n",
    "deep_rllib --play --pl 0.5 --session 1 --play-steps 2 results/rllib_results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plots the training results in a PDF-file\n",
    "plot_rllib results/rllib_results"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Bash",
   "language": "bash",
   "name": "bash"
  },
  "language_info": {
   "codemirror_mode": "shell",
   "file_extension": ".sh",
   "mimetype": "text/x-sh",
   "name": "bash"
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