rl_cart_pole_intro.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"./screenshots/cartpole_intro.png\" alt=\"drawing\" width=\"1000\"/>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gym\n",
    "\n",
    "import numpy as np\n",
    "from IPython.display import clear_output\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot(frame, rewards):\n",
    "    clear_output(True)\n",
    "    plt.figure(figsize=(20, 5))\n",
    "    plt.subplot(131)\n",
    "    plt.title(\"frame %s. reward: %s\" % (frame, np.mean(rewards[-10:])))\n",
    "    plt.plot(rewards)\n",
    "    plt.ylim(0, 200)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Random Action Policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "env = gym.make('CartPole-v0')\n",
    "\n",
    "all_rewards = []\n",
    "frame = 0\n",
    "\n",
    "for i_episode in range(100):\n",
    "    observation = env.reset()\n",
    "    episode_reward = 0\n",
    "    while True:\n",
    "        frame += 1\n",
    "        episode_reward += 1\n",
    "        env.render()\n",
    "        #random action taken\n",
    "        action = env.action_space.sample()\n",
    "        observation, reward, done, info = env.step(action)\n",
    "        if done:\n",
    "            #print(\"Episode finished after {} timesteps\".format(t+1))\n",
    "            all_rewards.append(episode_reward)\n",
    "            break\n",
    "        if frame % 200 == 0:\n",
    "            plot(frame, all_rewards)\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rule Based Policy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_action(observation):\n",
    "    cart_position = observation[0]\n",
    "    cart_velocity = observation[1]\n",
    "    pole_angle = observation[2]\n",
    "    pole_velocity_at_tip = observation[3]\n",
    "    if pole_angle < 0:\n",
    "        # push cart to left\n",
    "        return 0\n",
    "    else:\n",
    "        # push cart to right\n",
    "        return 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "env = gym.make('CartPole-v0')\n",
    "\n",
    "all_rewards = []\n",
    "frame = 0\n",
    "\n",
    "for i_episode in range(100):\n",
    "    observation = env.reset()\n",
    "    episode_reward = 0\n",
    "    while True:\n",
    "        frame += 1\n",
    "        episode_reward += 1\n",
    "        env.render()\n",
    "        #follow our rule\n",
    "        action = get_action(observation)\n",
    "        observation, reward, done, info = env.step(action)\n",
    "        if done:\n",
    "            #print(\"Episode finished after {} timesteps\".format(t+1))\n",
    "            all_rewards.append(episode_reward)\n",
    "            break\n",
    "        if frame % 200 == 0:\n",
    "            plot(frame, all_rewards)\n",
    "env.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}