q_learning_gymnasium.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "6aa37b81",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: gymnasium in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (0.29.1)\n",
      "Requirement already satisfied: numpy>=1.21.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium) (1.24.3)\n",
      "Requirement already satisfied: cloudpickle>=1.2.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium) (2.2.1)\n",
      "Requirement already satisfied: typing-extensions>=4.3.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium) (4.7.1)\n",
      "Requirement already satisfied: farama-notifications>=0.0.1 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium) (0.0.4)\n",
      "Requirement already satisfied: importlib-metadata>=4.8.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium) (6.0.0)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from importlib-metadata>=4.8.0->gymnasium) (3.11.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: gymnasium[toy-text] in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (0.29.1)\n",
      "Requirement already satisfied: numpy>=1.21.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium[toy-text]) (1.24.3)\n",
      "Requirement already satisfied: cloudpickle>=1.2.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium[toy-text]) (2.2.1)\n",
      "Requirement already satisfied: typing-extensions>=4.3.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium[toy-text]) (4.7.1)\n",
      "Requirement already satisfied: farama-notifications>=0.0.1 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium[toy-text]) (0.0.4)\n",
      "Requirement already satisfied: importlib-metadata>=4.8.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium[toy-text]) (6.0.0)\n",
      "Requirement already satisfied: pygame>=2.1.3 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from gymnasium[toy-text]) (2.5.2)\n",
      "Requirement already satisfied: zipp>=0.5 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from importlib-metadata>=4.8.0->gymnasium[toy-text]) (3.11.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: pygame in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (2.5.2)\n",
      "Note: you may need to restart the kernel to use updated packages.\n",
      "Requirement already satisfied: seaborn in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (0.12.2)\n",
      "Requirement already satisfied: numpy!=1.24.0,>=1.17 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from seaborn) (1.24.3)\n",
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      "Requirement already satisfied: matplotlib!=3.6.1,>=3.1 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from seaborn) (3.7.2)\n",
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      "Requirement already satisfied: cycler>=0.10 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (0.11.0)\n",
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      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (1.4.4)\n",
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      "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (9.4.0)\n",
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      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (2.8.2)\n",
      "Requirement already satisfied: importlib-resources>=3.2.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from matplotlib!=3.6.1,>=3.1->seaborn) (5.2.0)\n",
      "Requirement already satisfied: pytz>=2020.1 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from pandas>=0.25->seaborn) (2023.3.post1)\n",
      "Requirement already satisfied: tzdata>=2022.1 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from pandas>=0.25->seaborn) (2023.3)\n",
      "Requirement already satisfied: zipp>=3.1.0 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from importlib-resources>=3.2.0->matplotlib!=3.6.1,>=3.1->seaborn) (3.11.0)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\tobia\\anaconda3\\envs\\ktai\\lib\\site-packages (from python-dateutil>=2.7->matplotlib!=3.6.1,>=3.1->seaborn) (1.16.0)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "%pip install gymnasium\n",
    "%pip install gymnasium[toy-text]\n",
    "%pip install pygame\n",
    "%pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "4177bc80",
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "import random\n",
    "import os\n",
    "import re\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "np.set_printoptions(precision=3)\n",
    "np.random.seed(42)\n",
    "\n",
    "import gymnasium as gym\n",
    "import pygame\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "efaecf6e",
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.isdir(\"./q_tables/\"):\n",
    "    os.mkdir(\"./q_tables/\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "7e63b3e3",
   "metadata": {},
   "outputs": [],
   "source": [
    "env = gym.make(\"FrozenLake-v1\", render_mode='human') #move up a cell to not waste time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "409235fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Test game with random actions\n",
    "cur_state = env.reset() # reset environment and get initial state\n",
    "ret = 0.\n",
    "done = False\n",
    "i = 0\n",
    "while not done:\n",
    "    action = env.action_space.sample() # sample an action randomly\n",
    "    next_state, reward, done, truncated, info = env.step(action)\n",
    "    ret += reward\n",
    "    cur_state = next_state\n",
    "    time.sleep(0.01)\n",
    "    i += 1\n",
    "\n",
    "    if i == 50:\n",
    "        pygame.quit()\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0a2ae57e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def init_q_table():\n",
    "    return np.zeros([env.observation_space.n, env.action_space.n])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "8e1f60a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def epsilon_greedy_policy(q_table, current_state, epsilon):\n",
    "    if random.random() < epsilon:\n",
    "        action = env.action_space.sample() #exploration\n",
    "    else:\n",
    "        action = np.argmax(q_table[current_state]) #exploitation\n",
    "    return action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "54027c44",
   "metadata": {},
   "outputs": [],
   "source": [
    "def greedy_policy(q_table, current_state):\n",
    "    action = np.argmax(q_table[current_state])\n",
    "    return action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "3d7196c8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_nth_occurrence(string, old_char, new_char, n):\n",
    "    where = [m.start() for m in re.finditer(old_char, string)][n-1]\n",
    "    before = string[:where]\n",
    "    after = string[where:]\n",
    "    after = after.replace(old_char, new_char, 1)\n",
    "    new_string = before + after\n",
    "    return new_string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b04a5cb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def randomize_starting_position():\n",
    "    desc=[\"FFFF\", \"FHFH\", \"FFFH\", \"HFFG\"]\n",
    "    random_row_index = random.choice(range(len(desc)))\n",
    "    if \"F\" in desc[random_row_index]:\n",
    "        f_count = desc[random_row_index].count(\"F\")   \n",
    "        random_f = random.randint(1, f_count)\n",
    "        \n",
    "        new_random_row = replace_nth_occurrence(desc[random_row_index], \"F\", \"S\", random_f)\n",
    "        desc[random_row_index] = new_random_row\n",
    "        return desc\n",
    "    else:\n",
    "        randomize_starting_position()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "3a93cdd0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train(q_table, gamma, alpha, epsilon, iterations, name, slippery_param):\n",
    "    start_time = time.time()\n",
    "        \n",
    "    env = gym.make(\"FrozenLake-v1\", is_slippery=slippery_param)\n",
    "\n",
    "    epochs_total = []\n",
    "    rewards_total = []\n",
    "    \n",
    "    for i in range(iterations):\n",
    "        current_state = env.reset()[0]\n",
    "\n",
    "        epochs, reward, rewards = 0, 0, 0\n",
    "        done = False\n",
    "\n",
    "        while not done:\n",
    "            action = epsilon_greedy_policy(q_table, current_state, epsilon)\n",
    "            next_state, reward, done, truncated, info = env.step(action)\n",
    "\n",
    "            q_table[current_state][action] = q_table[current_state][action] + \\\n",
    "                alpha * (reward + gamma * np.max(q_table[next_state]) - q_table[current_state][action])\n",
    "\n",
    "            rewards += reward \n",
    "            current_state = next_state\n",
    "\n",
    "            epochs += 1\n",
    "\n",
    "        epochs_total.append(epochs)\n",
    "        rewards_total.append(rewards)\n",
    "\n",
    "\n",
    "        if i % 1000 == 0:\n",
    "            print(f\"Episode: {i}, rewards:{rewards}\")\n",
    "    \n",
    "    runtime = time.time() - start_time\n",
    "\n",
    "    print(\"Training finished.\\n\")\n",
    "    \n",
    "    #save trained q_table\n",
    "    np.save(f\"./q_tables/{name}.npy\", q_table)\n",
    "    \n",
    "    #logging stuff\n",
    "    avg_reward = np.average(rewards_total)\n",
    "    max_reward = max(rewards_total)\n",
    "    min_reward = min(rewards_total)\n",
    "    \n",
    "    with open(f\"./q_logging.txt\", \"a\") as f:\n",
    "        f.write(f\"Epsilon:{epsilon}, gamma:{gamma}, alpha:{alpha}, avg_reward: {avg_reward}, max_reward: {max_reward}, min_reward:{min_reward}, runtime: {runtime}\\n\")\n",
    "    \n",
    "    return q_table, epochs_total, rewards_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "dc64dc38",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_random_starting_position(q_table, gamma, alpha, epsilon, iterations, name):\n",
    "    start_time = time.time()\n",
    "    \n",
    "    starting_position = randomize_starting_position()\n",
    "\n",
    "    epochs_total = []\n",
    "    rewards_total = []\n",
    "    \n",
    "    for i in range(iterations):\n",
    "        starting_position = randomize_starting_position()\n",
    "        env = gym.make(\"FrozenLake-v1\", is_slippery=False, desc=starting_position)\n",
    "        current_state = env.reset()[0]\n",
    "\n",
    "        epochs, reward, rewards = 0, 0, 0\n",
    "        done = False\n",
    "\n",
    "        while not done:\n",
    "            action = epsilon_greedy_policy(q_table, current_state, epsilon)\n",
    "            next_state, reward, done, truncated, info = env.step(action)\n",
    "\n",
    "            q_table[current_state][action] = q_table[current_state][action] + \\\n",
    "                alpha * (reward + gamma * np.max(q_table[next_state]) - q_table[current_state][action])\n",
    "\n",
    "            rewards += reward \n",
    "            current_state = next_state\n",
    "\n",
    "            epochs += 1\n",
    "\n",
    "        epochs_total.append(epochs)\n",
    "        rewards_total.append(rewards)\n",
    "\n",
    "\n",
    "        if i % 1000 == 0:\n",
    "            print(starting_position)\n",
    "            print(f\"Episode: {i}, rewards:{rewards}\")\n",
    "    \n",
    "    runtime = time.time() - start_time\n",
    "\n",
    "    print(\"Training finished.\\n\")\n",
    "    \n",
    "    #save trained q_table\n",
    "    np.save(f\"./q_tables/{name}.npy\", q_table)\n",
    "    \n",
    "    #logging stuff\n",
    "    avg_reward = np.average(rewards_total)\n",
    "    max_reward = max(rewards_total)\n",
    "    min_reward = min(rewards_total)\n",
    "    \n",
    "    with open(f\"./q_logging.txt\", \"a\") as f:\n",
    "        f.write(f\"Epsilon:{epsilon}, gamma:{gamma}, alpha:{alpha}, avg_reward: {avg_reward}, max_reward: {max_reward}, min_reward:{min_reward}, runtime: {runtime}\\n\")\n",
    "    \n",
    "    return q_table, epochs_total, rewards_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "40a6bf5e",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_epsilon_decay(q_table, gamma, alpha, epsilon, iterations, name):\n",
    "    start_time = time.time()\n",
    "    \n",
    "    env = gym.make(\"FrozenLake-v1\")\n",
    "\n",
    "    epochs_total = []\n",
    "    rewards_total = []\n",
    "    \n",
    "    for i in range(iterations):\n",
    "        current_state = env.reset()[0]\n",
    "\n",
    "        epochs, reward, rewards = 0, 0, 0\n",
    "        done = False\n",
    "\n",
    "        while not done:\n",
    "            action = epsilon_greedy_policy(q_table, current_state, epsilon)\n",
    "            next_state, reward, done, truncated, info = env.step(action)\n",
    "\n",
    "            q_table[current_state][action] = q_table[current_state][action] + \\\n",
    "                alpha[i] * (reward + gamma * np.max(q_table[next_state]) - q_table[current_state][action])\n",
    "\n",
    "            rewards += reward \n",
    "            current_state = next_state\n",
    "\n",
    "            epochs += 1\n",
    "\n",
    "        epochs_total.append(epochs)\n",
    "        rewards_total.append(rewards)\n",
    "\n",
    "\n",
    "        if i % 1000 == 0:\n",
    "            print(f\"Episode: {i}, rewards:{rewards}\")\n",
    "    \n",
    "    runtime = time.time() - start_time\n",
    "\n",
    "    print(\"Training finished.\\n\")\n",
    "    \n",
    "    #save trained q_table\n",
    "    np.save(f\"./q_tables/{name}.npy\", q_table)\n",
    "    \n",
    "    #logging stuff\n",
    "    avg_reward = np.average(rewards_total)\n",
    "    max_reward = max(rewards_total)\n",
    "    min_reward = min(rewards_total)\n",
    "    \n",
    "    with open(f\"./q_logging.txt\", \"a\") as f:\n",
    "        f.write(f\"Epsilon:{epsilon}, gamma:{gamma}, alpha:{alpha[i]}, avg_reward: {avg_reward}, max_reward: {max_reward}, min_reward:{min_reward}, runtime: {runtime}\\n\")\n",
    "    \n",
    "    return q_table, epochs_total, rewards_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "b55631e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def q_table_directions_map(q_table, map_size):\n",
    "    q_table_val_max = q_table.max(axis=1).reshape(map_size, map_size)\n",
    "    q_table_best_action = np.argmax(q_table, axis=1).reshape(map_size, map_size)\n",
    "    directions = {0: \"←\", 1: \"↓\", 2: \"→\", 3: \"↑\"}\n",
    "    q_table_directions = np.empty(q_table_best_action.flatten().shape, dtype=str)\n",
    "    eps = np.finfo(float).eps\n",
    "    \n",
    "    for idx, val in enumerate(q_table_best_action.flatten()):\n",
    "        if q_table_val_max.flatten()[idx] > eps:\n",
    "            q_table_directions[idx] = directions[val]\n",
    "    q_table_directions = q_table_directions.reshape(map_size, map_size)\n",
    "    \n",
    "    return q_table_val_max, q_table_directions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "77d9e8a7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_q_values_map(q_table, env, map_size):\n",
    "    q_table_val_max, q_table_directions = q_table_directions_map(q_table, map_size)\n",
    "\n",
    "    sns.heatmap(\n",
    "        q_table_val_max,\n",
    "        annot=q_table_directions,\n",
    "        fmt=\"\",\n",
    "        cmap=sns.color_palette(\"Blues\", as_cmap=True),\n",
    "    ).set(title=\"Q-values and best action\")\n",
    "\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "d13affb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "#play a game with trained q_table\n",
    "def play_game(q_table):\n",
    "    time.sleep(2)\n",
    "\n",
    "    env = gym.make(\"FrozenLake-v1\", render_mode=\"human\")\n",
    "    \n",
    "    state = env.reset()[0]\n",
    "    done = False\n",
    "\n",
    "    while not done:\n",
    "        time.sleep(0.1)\n",
    "        action = np.argmax(q_table[state])\n",
    "        state, reward, done, truncated, info = env.step(action)\n",
    "\n",
    "    pygame.quit()  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a1a50ed9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_epochs_rewards(epochs_total, rewards_total):\n",
    "    plt.figure(1)\n",
    "    \n",
    "    plt.subplot(211)\n",
    "    plt.plot(epochs_total)\n",
    "    plt.title('Evolution of number of steps')\n",
    "    plt.ylabel('Number of steps')\n",
    "    plt.xlabel('epsiode')\n",
    "    \n",
    "    plt.subplot(212)\n",
    "    plt.plot(rewards_total,'r')\n",
    "    plt.title('Evolution of total reward')\n",
    "    plt.ylabel('Rewards')\n",
    "    plt.xlabel('epsiode')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "92725ae1",
   "metadata": {},
   "source": [
    "## Default params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "1da3dab7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Default hyperparameters\n",
    "\n",
    "# gamma discount factor\n",
    "gamma = 0.9\n",
    "# alpha learning rate\n",
    "alpha = 0.1\n",
    "# epsilon greedy exploration parameter\n",
    "epsilon = 0.5\n",
    "#max steps per episode\n",
    "iterations = 3000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "dbb97a4b",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train\n",
    "default_val_table = init_q_table()\n",
    "default_val_table, epochs_total, rewards_total = train(default_val_table, gamma, alpha, epsilon, iterations, \"default params\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "33ad1222",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 128.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "439990d6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d9077988",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(default_val_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f9de91b4",
   "metadata": {},
   "source": [
    "<p>Here we see the agent trying the moves he knows are safe quite often but he will try a new (unsafe) move and this results in learning how to do the level.</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a342ace",
   "metadata": {},
   "source": [
    "## Low epsilon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "39bcb6a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with low epsilon\n",
    "epsilon = 0.1\n",
    "low_epsilon_q_table = init_q_table()\n",
    "low_epsilon_q_table, epochs_total, rewards_total = train(low_epsilon_q_table, gamma, alpha, epsilon, iterations, \"low_epsilon\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "f3c0aaff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 0.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "74dee3b9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "710ef250",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(low_epsilon_q_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2866d237",
   "metadata": {},
   "source": [
    "<p>Here we see that the agent doesn't really go further than the one move he knows (1 tile down) this is exactly what you'd expect from setting a very low epsilon meaning that the agent doesn't explore and thus won't learn. This is clearly indicated in the reward graph staying a constant 0</p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c85607a",
   "metadata": {},
   "source": [
    "## High epsilon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "5500f714",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with high epsilon\n",
    "epsilon = 1\n",
    "high_epsilon_q_table = init_q_table()\n",
    "high_epsilon_q_table, epochs_total, rewards_total = train(high_epsilon_q_table, gamma, alpha, epsilon, iterations, \"high_epsilon\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "1cd65cb4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 38.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "af11a061",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "d4074619",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(high_epsilon_q_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffacf66e",
   "metadata": {},
   "source": [
    "<p>In this case the epsilon is really high so the agent only tries new things without exploiting known moves, this translates well into the reward graph where we can see that the agent only occasionally finishes the level (when he gets luck) but doesn't learn how to do it<p>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "994f485a",
   "metadata": {},
   "source": [
    "## Epsilon decay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "377bff43",
   "metadata": {},
   "outputs": [],
   "source": [
    "#hyperparam\n",
    "epsilon = 1\n",
    "decay = 0.001\n",
    "min_epsilon = 0.01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d62515e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_with_decay(q_table, gamma, alpha, epsilon, iterations, name, decay, min_epsilon):\n",
    "    start_time = time.time()\n",
    "    \n",
    "    env = gym.make(\"FrozenLake-v1\")\n",
    "\n",
    "    epochs_total = []\n",
    "    rewards_total = []\n",
    "    \n",
    "    for i in range(iterations):\n",
    "        current_state = env.reset()[0]\n",
    "\n",
    "        epochs, reward, rewards = 0, 0, 0\n",
    "        done = False\n",
    "\n",
    "        while not done:\n",
    "            action = epsilon_greedy_policy(q_table, current_state, epsilon)\n",
    "            next_state, reward, done, truncated, info = env.step(action)\n",
    "\n",
    "            q_table[current_state][action] = q_table[current_state][action] + \\\n",
    "                alpha * (reward + gamma * np.max(q_table[next_state]) - q_table[current_state][action])\n",
    "\n",
    "            rewards += reward \n",
    "            current_state = next_state\n",
    "\n",
    "            epochs += 1\n",
    "        \n",
    "        epsilon = max(min_epsilon, epsilon - decay) #added epsilon decay\n",
    "\n",
    "        epochs_total.append(epochs)\n",
    "        rewards_total.append(rewards)\n",
    "\n",
    "\n",
    "        if i % 1000 == 0:\n",
    "            print(f\"Episode: {i}, rewards:{rewards}\")\n",
    "    \n",
    "    runtime = time.time() - start_time\n",
    "\n",
    "    print(\"Training finished.\\n\")\n",
    "    \n",
    "    #save trained q_table\n",
    "    np.save(f\"./q_tables/{name}.npy\", q_table)\n",
    "    \n",
    "    #logging stuff\n",
    "    avg_reward = np.average(rewards_total)\n",
    "    max_reward = max(rewards_total)\n",
    "    min_reward = min(rewards_total)\n",
    "    \n",
    "    with open(f\"./q_logging.txt\", \"a\") as f:\n",
    "        f.write(f\"Epsilon:{epsilon}, gamma:{gamma}, alpha:{alpha}, avg_reward: {avg_reward}, max_reward: {max_reward}, min_reward:{min_reward}, runtime: {runtime}\\n\")\n",
    "    \n",
    "    return q_table, epochs_total, rewards_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "30aecb94",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with high epsilon\n",
    "decay_q_table = init_q_table()\n",
    "decay_q_table, epochs_total, rewards_total = train_with_decay(decay_q_table, gamma, alpha, epsilon, iterations, \"epsilon decay\", decay, min_epsilon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "ee184383",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "6005d0c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(decay_q_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "649d8cc5",
   "metadata": {},
   "source": [
    "<p>Judging from the game I watched and the reward graph/ logging stats we can see that this method works a lot better. The avg reward is 0.38 compared to the previous best of 0.06. <br> It seems logical that letting the agent learn a lot in the beginning via exploration and when the agent has learned enough focus more on exploiting is a more efficient way of learning</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "c9df7046",
   "metadata": {},
   "outputs": [],
   "source": [
    "episodes =  [i for i in range(0,3000)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "c286588e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1da9d134940>]"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(episodes, rewards_total)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff830d88",
   "metadata": {},
   "source": [
    "## Low gamma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "12bdf459",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with low gamma\n",
    "gamma = 0\n",
    "low_gamma_q_table = init_q_table()\n",
    "low_gamma_q_table, epochs_total, rewards_total = train(low_gamma_q_table, gamma, alpha, epsilon, iterations, \"low_gamma\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "371854af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 37.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "59b5faec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "5a2c4c90",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37.0\n"
     ]
    }
   ],
   "source": [
    "print(sum(rewards_total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "ea7dcf8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(low_gamma_q_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "45977a38",
   "metadata": {},
   "source": [
    "<p>Here we see that the agent doesn't really go further than the one move he knows (1 tile down) this is exactly what you'd expect from setting a very low epsilon meaning that the agent doesn't explore and thus won't learn. This is clearly indicated in the reward graph staying a constant 0</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "f22fc81c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.613666666666667\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(epochs_total))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8151511",
   "metadata": {},
   "source": [
    "## High gamma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "6637495a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with high gamma\n",
    "gamma = 1\n",
    "high_gamma_q_table = init_q_table()\n",
    "high_gamma_q_table, epochs_total, rewards_total = train(high_gamma_q_table, gamma, alpha, epsilon, iterations, \"high_gamma\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "e00d3925",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 37.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "c1bd2a34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "27803958",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(high_gamma_q_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8e2006a",
   "metadata": {},
   "source": [
    "<p>In this case the epsilon is really high so the agent only tries new things without exploiting known moves, this translates well into the reward graph where we can see that the agent only occasionally finishes the level (when he gets luck) but doesn't learn how to do it<p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "244fd69a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.722\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(epochs_total))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c262374",
   "metadata": {},
   "source": [
    "## Medium gamma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "342ded16",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with medium gamma\n",
    "gamma = 0.5\n",
    "medium_gamma_q_table = init_q_table()\n",
    "medium_gamma_q_table, epochs_total, rewards_total = train(medium_gamma_q_table, gamma, alpha, epsilon, iterations, \"medium_gamma\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "93801275",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 46.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "f4a13ecf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9bc6f0bb",
   "metadata": {},
   "source": [
    "## Low alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "ef983d0e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with low alpha\n",
    "alpha = 0.1\n",
    "low_alpha_q_table = init_q_table()\n",
    "low_alpha_q_table, epochs_total, rewards_total = train(low_alpha_q_table, gamma, alpha, epsilon, iterations, \"low_alpha\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "ef72528b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 43.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "4f363e04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "5a163f42",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(low_alpha_q_table)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "146a6c3b",
   "metadata": {},
   "source": [
    "## High alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "57cceae1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with high alpha\n",
    "alpha = 1\n",
    "high_alpha_q_table = init_q_table()\n",
    "high_alpha_q_table, epochs_total, rewards_total = train(high_alpha_q_table, gamma, alpha, epsilon, iterations, \"high_alpha\", True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "9b4bae8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 40.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "e77a6d23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "91b91f66",
   "metadata": {},
   "outputs": [],
   "source": [
    "play_game(high_alpha_q_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "7522a924",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7.798\n"
     ]
    }
   ],
   "source": [
    "print(np.mean(epochs_total))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "3097b29c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_alpha_schedule(num_episodes, alpha_start=1.0, alpha_decay=0.99, alpha_min=0.01):\n",
    "    x = np.arange(num_episodes)+1\n",
    "    y = np.full(num_episodes, alpha_start)\n",
    "    y = np.maximum((alpha_decay**x)*alpha_start, alpha_min)\n",
    "    return y\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "33576443",
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_schedule = create_alpha_schedule(iterations)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "2089c08e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.99 0.98 0.97 ... 0.01 0.01 0.01]\n"
     ]
    }
   ],
   "source": [
    "print(alpha_schedule)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "30f65680",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train with high alpha\n",
    "alpha = alpha_schedule\n",
    "high_alpha_q_table = init_q_table()\n",
    "high_alpha_q_table, epochs_total, rewards_total = train_epsilon_decay(high_alpha_q_table, gamma, alpha, epsilon, iterations, \"high_alpha\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "0d862c27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 38.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "dca448a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "25cc90ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "    plt.plot(alpha,'b')\n",
    "    plt.ylabel('Alpha')\n",
    "    plt.xlabel('epsiode')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d214277",
   "metadata": {},
   "source": [
    "## Non-slippery tiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "e35a21c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Default hyperparameters\n",
    "\n",
    "# gamma discount factor\n",
    "gamma = 0.9\n",
    "# alpha learning rate\n",
    "alpha = 0.1\n",
    "# epsilon greedy exploration parameter\n",
    "epsilon = 0.5\n",
    "#max steps per episode\n",
    "iterations = 3000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "42e4f277",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train\n",
    "default_val_table = init_q_table()\n",
    "default_val_table, epochs_total, rewards_total = train(default_val_table, gamma, alpha, epsilon, iterations, \"default params non-slippery\", False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "470b35ae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total rewards after 3k episodes: 999.0\n"
     ]
    }
   ],
   "source": [
    "print(f\"Total rewards after 3k episodes: {sum(rewards_total)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "22b45c66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_epochs_rewards(epochs_total, rewards_total)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d934254e",
   "metadata": {},
   "source": [
    "## Heatmap of traversed cells"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "3ea90d9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "def train_with_action_logging(q_table, gamma, alpha, epsilon, iterations, name, action_log):\n",
    "    start_time = time.time()\n",
    "    \n",
    "    env = gym.make(\"FrozenLake-v1\")\n",
    "\n",
    "    epochs_total = []\n",
    "    rewards_total = []\n",
    "    \n",
    "    for i in range(iterations):\n",
    "        \n",
    "        current_state = env.reset()[0]\n",
    "\n",
    "        epochs, reward, rewards = 0, 0, 0\n",
    "        done = False\n",
    "        action_per_game = []\n",
    "        while not done:\n",
    "            action = epsilon_greedy_policy(q_table, current_state, epsilon)\n",
    "            action_per_game.append(action)\n",
    "            next_state, reward, done, truncated, info = env.step(action)\n",
    "\n",
    "            q_table[current_state][action] = q_table[current_state][action] + \\\n",
    "                alpha * (reward + gamma * np.max(q_table[next_state]) - q_table[current_state][action])\n",
    "\n",
    "            rewards += reward \n",
    "            current_state = next_state\n",
    "\n",
    "            epochs += 1\n",
    "\n",
    "        epochs_total.append(epochs)\n",
    "        rewards_total.append(rewards)\n",
    "\n",
    "        action_log.append(action_per_game)\n",
    "        \n",
    "        if i % 1000 == 0:\n",
    "            print(f\"Episode: {i}, rewards:{rewards}\")\n",
    "    \n",
    "    runtime = time.time() - start_time\n",
    "\n",
    "    print(\"Training finished.\\n\")\n",
    "    \n",
    "    #save trained q_table\n",
    "    np.save(f\"./q_tables/{name}.npy\", q_table)\n",
    "    \n",
    "    #logging stuff\n",
    "    avg_reward = np.average(rewards_total)\n",
    "    max_reward = max(rewards_total)\n",
    "    min_reward = min(rewards_total)\n",
    "    \n",
    "    with open(f\"./q_logging.txt\", \"a\") as f:\n",
    "        f.write(f\"Epsilon:{epsilon}, gamma:{gamma}, alpha:{alpha}, avg_reward: {avg_reward}, max_reward: {max_reward}, min_reward:{min_reward}, runtime: {runtime}\\n\")\n",
    "    \n",
    "    return q_table, epochs_total, rewards_total"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "bf3878bc",
   "metadata": {},
   "outputs": [],
   "source": [
    "action_log = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "eff0c694",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# gamma discount factor\n",
    "gamma = 0.9\n",
    "# alpha learning rate\n",
    "alpha = 0.1\n",
    "# epsilon greedy exploration parameter\n",
    "epsilon = 0.5\n",
    "#max steps per episode\n",
    "iterations = 3000\n",
    "\n",
    "default_val_table = init_q_table()\n",
    "default_val_table, epochs_total, rewards_total = train_with_action_logging(default_val_table, gamma, alpha, epsilon, iterations, \"default params\", action_log)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "a87bfd09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]"
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "GAME_GRID = [[0,0,0,0],[0,0,0,0],[0,0,0,0],[0,0,0,0]]\n",
    "GAME_GRID"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "792b4851",
   "metadata": {},
   "outputs": [],
   "source": [
    "def next_move(step, cur_row, cur_col):\n",
    "    if step == 0:\n",
    "        return cur_row, cur_col-1\n",
    "    if step == 1:\n",
    "        return cur_row+1, cur_col\n",
    "    if step == 2:\n",
    "        return cur_row, cur_col+1\n",
    "    if step == 3:\n",
    "        return cur_row-1, cur_col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "7ee63f08",
   "metadata": {},
   "outputs": [],
   "source": [
    "def map_step(step):\n",
    "    if step == 0:\n",
    "        return \"left\"\n",
    "    if step == 1:\n",
    "        return \"down\"\n",
    "    if step == 2:\n",
    "        return 'right'\n",
    "    if step == 3:\n",
    "        return \"up\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "be51c0a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "for game in action_log:\n",
    "    cur_col, cur_row = 0, 0\n",
    "    for step in game:\n",
    "        \n",
    "        row, col = next_move(step, cur_row, cur_col)\n",
    "        \n",
    "        if col <= 3 and col >= 0:\n",
    "            cur_col = col\n",
    "        \n",
    "        if row <= 3 and row >= 0:\n",
    "            cur_row = row\n",
    "        \n",
    "        GAME_GRID[cur_row][cur_col] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "296c8a62",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(GAME_GRID, cmap=\"crest\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f65843b3",
   "metadata": {},
   "source": [
    "## Hyperparameter Heatmap"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "0e5ab906",
   "metadata": {},
   "outputs": [],
   "source": [
    "alpha_options=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]\n",
    "epsilon_options=[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "ff000518",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alpha: 0.1\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:1.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:1.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "    Alpha  Epsilon  Rewards total\n",
      "0     0.1      0.1            0.0\n",
      "1     0.1      0.2           56.0\n",
      "2     0.1      0.3          279.0\n",
      "3     0.1      0.4          202.0\n",
      "4     0.1      0.5          185.0\n",
      "..    ...      ...            ...\n",
      "95    1.0      0.6           73.0\n",
      "96    1.0      0.7           60.0\n",
      "97    1.0      0.8           56.0\n",
      "98    1.0      0.9           48.0\n",
      "99    1.0      1.0           45.0\n",
      "\n",
      "[100 rows x 3 columns]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = []\n",
    "for alpha_param in alpha_options:\n",
    "    for epsilon_param in epsilon_options:\n",
    "        print(\"Alpha: \" + str(alpha_param))\n",
    "        print(\"Epsilon: \" + str(epsilon_param))\n",
    "        heatmap_val_table = init_q_table()\n",
    "        heatmap_val_table, epochs_total, rewards_total = train(heatmap_val_table, gamma, alpha_param, epsilon_param, iterations, \"heatmap\", True)\n",
    "        results.append([alpha_param, epsilon_param, sum(rewards_total)])\n",
    "        \n",
    "results = np.array(results)\n",
    "\n",
    "df = pd.DataFrame(results, columns=['Alpha', 'Epsilon', 'Rewards total'])\n",
    "\n",
    "print(df)\n",
    "\n",
    "df_pivot = df.pivot(index='Epsilon', columns='Alpha', values='Rewards total')\n",
    "\n",
    "# Create a heatmap using seaborn\n",
    "sns.set(rc={\"figure.figsize\":(10, 10)}) #width=8, height=4\n",
    "sns.heatmap(df_pivot, cmap='Blues', annot=True, fmt='.1f')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "a51a5d47",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alpha: 0.1\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.1\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.2\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.3\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.4\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.5\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.6\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.7\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.8\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:1.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 0.9\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.2\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.3\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.4\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.5\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.6\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.7\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.8\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 0.9\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "Alpha: 1\n",
      "Epsilon: 1\n",
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:0.0\n",
      "Training finished.\n",
      "\n",
      "    Alpha  Epsilon  Rewards total\n",
      "0     0.1      0.1            0.0\n",
      "1     0.1      0.2            0.0\n",
      "2     0.1      0.3            0.0\n",
      "3     0.1      0.4            0.0\n",
      "4     0.1      0.5          140.0\n",
      "..    ...      ...            ...\n",
      "95    1.0      0.6          360.0\n",
      "96    1.0      0.7          471.0\n",
      "97    1.0      0.8          287.0\n",
      "98    1.0      0.9          126.0\n",
      "99    1.0      1.0           40.0\n",
      "\n",
      "[100 rows x 3 columns]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = []\n",
    "for alpha_param in alpha_options:\n",
    "    for epsilon_param in epsilon_options:\n",
    "        print(\"Alpha: \" + str(alpha_param))\n",
    "        print(\"Epsilon: \" + str(epsilon_param))\n",
    "        heatmap_val_table = init_q_table()\n",
    "        heatmap_val_table, epochs_total, rewards_total = train(heatmap_val_table, gamma, alpha_param, epsilon_param, iterations, \"heatmap\", False)\n",
    "        results.append([alpha_param, epsilon_param, sum(rewards_total)])\n",
    "        \n",
    "results = np.array(results)\n",
    "\n",
    "df = pd.DataFrame(results, columns=['Alpha', 'Epsilon', 'Rewards total'])\n",
    "\n",
    "print(df)\n",
    "\n",
    "df_pivot = df.pivot(index='Epsilon', columns='Alpha', values='Rewards total')\n",
    "\n",
    "# Create a heatmap using seaborn\n",
    "sns.set(rc={\"figure.figsize\":(10, 10)}) #width=8, height=4\n",
    "sns.heatmap(df_pivot, cmap='Blues', annot=True, fmt='.1f')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebaeaa63",
   "metadata": {},
   "source": [
    "## Best actions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "1b4e82cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Default hyperpram\n",
    "\n",
    "# gamma discount factor\n",
    "gamma = 0.9\n",
    "# alpha learning rate\n",
    "alpha = 0.1\n",
    "# epsilon greedy exploration parameter\n",
    "epsilon = 0.5\n",
    "#max steps per episode\n",
    "iterations = 3000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "3cca0ce4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 0, rewards:0.0\n",
      "Episode: 1000, rewards:0.0\n",
      "Episode: 2000, rewards:1.0\n",
      "Training finished.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#train\n",
    "default_val_table = init_q_table()\n",
    "default_val_table, epochs_total, rewards_total = train(default_val_table, gamma, alpha, epsilon, iterations, \"default params\", False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "59e43465",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bbrvF7373u7j33ntj2LBhNc8HYPMTFGAr961vfSs+97nPxW233RaXX355LF68OHbcccc46qijYrfddoubb7455s6dG5dddtl6d6n5sCOPPDKmTZsWhx12WK3fUh900EExevTouOWWW+I3v/lN7LjjjnHQQQfFddddF2eccUY899xz0bdv3+TznX/++bF69eqYMGFCbLPNNvGVr3wlRo0aVWt70N69e8fUqVPjuuuuixEjRkTDhg2jU6dOccstt9RUXc4888woLS2Ne++9N66//vpo1qxZ9OvXL0aNGrXBr+Xyyy+PSy+9NC699NKI+GAnoTFjxsT9999fc4NyXV188cWx4447xh133BFLliyJPn36xKmnnhpXX331xz73tNNOi5kzZ8app54azZo1i5NPPjmGDRtW8/g3vvGN2HbbbePmm2+Ou+++O5o0aRIHHHBATJw4MXbbbbeI+OCH+6uvvjqmTZsWCxcujB122CEGDhxY8yZ7TZs2jW9961tx9913x+OPPx5PPPFEUseq6/dw0KBB0aRJk5g6dWrcc8890apVqzjppJPilFNOqfk8vXr1iiuvvDKeeuqpmhvE12ncuHH8+Mc/jiuvvDImT54cy5Yti3bt2sVll10WAwcO3KjXHYBPplD9n3flAXzI3Llz48c//nEMGzas5p4DACD/BAUAACDhZmYAANiCTJkyJY4//viPPGfx4sUxatSo6NatW3Tr1i2+973v1do5sC4EBQAA2ELceuutMXny5I89b8SIEfHmm2/WnP/EE0+s9z13PoqbmQEAoJ5bsGBBXHjhhfHcc89F27ZtP/Lc559/Pp555pl4+OGHa3aXGzt2bJx88skxcuTIaNWqVZ2uaaIAAAD13Isvvhjbbbdd3H///evdxvrDnn322dhpp51qbUHdvXv3KBQKH/tGpx9mogAAAJ+C/v37f+Tj//mGlR/Wr1+/6NevX52us2DBgthll11qHSstLY3tt98+5s2bV6fPEVFPg8IRN84o9hLYSuzQvKzYS2ArMfO1RcVeAluJs/9rr2Ivga3ENz63a7GXsEGNuwz7+JOKoNf63+MzcytWrEjeDyciolGjRlFZWVnnz1MvgwIAAOTNR00MslRWVhZVVVXJ8crKymjSpEmdP497FAAAIEfKy8ujoqKi1rGqqqp4991363wjc4SgAABA3hRK6ufHp6Rbt24xf/78mD17ds2xp59+OiIiDjjggDp/HkEBAAC2YGvWrImFCxfGypUrIyKic+fOccABB8RZZ50Vf/vb3+Ivf/lLXHzxxXHUUUeZKAAAwNZi3rx50bt373j44YcjIqJQKMR1110Xbdq0iRNOOCG+853vxMEHHxyXXHLJRn1eNzMDAJAvhUKxV7BZXX755bX+3qZNm3j55ZdrHdthhx3q9A7OH8VEAQAASAgKAABAQvUIAIB8+RR3GMozryIAAJAQFAAAgITqEQAA+ZLzXY8+LSYKAABAQlAAAAASqkcAAOSLXY8y4VUEAAASggIAAJBQPQIAIF/sepQJEwUAACAhKAAAAAnVIwAA8sWuR5nwKgIAAAlBAQAASKgeAQCQL3Y9yoSJAgAAkBAUAACAhOoRAAD5YtejTHgVAQCAhKAAAAAkVI8AAMgXux5lwkQBAABICAoAAEBC9QgAgHyx61EmvIoAAEBCUAAAABKqRwAA5ItdjzJhogAAACQEBQAAIKF6BABAvtj1KBNeRQAAICEoAAAACdUjAADyRfUoE15FAAAgISgAAAAJ1SMAAPKlxBuuZcFEAQAASAgKAABAQvUIAIB8setRJryKAABAQlAAAAASqkcAAORLwa5HWTBRAAAAEoICAACQUD0CACBf7HqUCa8iAACQEBQAAICE6hEAAPli16NMmCgAAAAJQQEAAEioHgEAkC92PcqEVxEAAEgICgAAQEL1CACAfLHrUSZMFAAAgISgAAAAJFSPAADIF7seZcKrCAAAJAQFAAAgoXoEAEC+2PUoEyYKAABAQlAAAAASqkcAAOSLXY8y4VUEAAASggIAAJBQPQIAIF/sepQJEwUAACAhKAAAAAnVIwAA8sWuR5nwKgIAAAlBAQAASKgeAQCQL6pHmfAqAgAACUEBAABIqB4BAJAv3nAtEyYKAABAQlAAAAASqkcAAOSLXY8y4VUEAAASggIAAJAQFHJi312axdDP717sZQBk5oDdt4uzv/iZYi8D2BIVCvXzYwsjKAAAAAlBAQAASNj1CACAfLHrUSY2KiisXr06HnnkkXj22Wdj7ty5UVVVFY0bN47y8vLo2rVrDBgwILbZRvaAPGncsCR2aNIw5iypLPZSADKx8v1l8e7bFVG+e7tiLwXqtTrHrTfeeCMOO+ywuOCCC2LWrFlRVlYWO+20UzRs2DBeeumlOP/88+OII46IuXPnbs71Ap+ism1K4jsH7xlrq4u9EoBsrHx/efz4iguisAXeWAqftjr/+n/MmDHRpk2buOeee6JZs2bJ40uXLo2zzjorxo4dGzfccEOmiwQ+fa2alsYZvXeP/33rvZi71DQB2PK9PW9O/PSqi6PDgT2j1W5ti70cNidBMBN1DgrPPfdc3H333esNCRERzZs3j3POOScGDRqU2eKA4mjXsnGc169dlG5TEg0KhejSuvlGPf97v3llM60MYNO8+crMmDrmrFi9qirWrl4dL814YqOeP+LKWzbTyqD+qnNQaN68eVRUVMTee++9wXPmzp0bZWVlmSwMKJ5/L1oR1z/xRpzYvXU88s+34w+vLi72kgA+kd326hjHjrwkfnnjldHrsIHR7dDDi70kqPfqfI/CwIED4/zzz4+f/exnMXv27KiqqoqIiKqqqnjzzTfj3nvvjQsvvDCOPvrozbZY4NPzt3nvxbjpr8ahe+0YLRrbpADY8u19QM8YOu76+MtvfhFL3llY7OWwGRUKhXr5saWp8//9hw8fHiUlJXHFFVfE+++/nzy+7bbbxqBBg+LMM8/MdIF8tK67bRf/+9bSWsc+17p5vFyxLFasWlukVZEXi95fFVf/6fXYuWmjWLxidbGXw1bi8+1bxjOv155idd+zRfxj7tJ4v2pNkVZFXmy/Y6sYfO73Y9GCt2K7HXYq9nKgXqtzUCgUCjFs2LAYOnRovPTSS7FgwYJYsWJFlJWVRXl5eXTo0CFKS0s351pZj4YNSmLS0R3jsZffjialDeL8AZ+Jd1esSsIDbKp3lq+Kd5avKvYy2Io0bFASt33rwHjwb/OjaaNt4vKjO8ai5auS8ACbqsXO5dFi5/JiLwPqvY3uEzRs2DD233//zbEWNsFTry+ObRoUYlS/dlFSKMSjLy+MH/55drGXBbDJHv/n29GwQSHGHrlPlBQK8eDf5scPfusGeaDutsSaT32keJwDf3p1UXRo1TS67rZd3CAkADkw/aWFsV+b5tGr/Q5CAkCRCAo5ceezb8X0WQujao13xgLy4cY/vh4PvDA/Kle73wqgGASFnFhetSaWL1pR7GUAZGZZ5Zp4pWJ5sZcBbIk0jzJR5+1RAQCArYegAAAAJFSPAADIFbseZcNEAQAASAgKAABAQvUIAIBcUT3KhokCAACQEBQAAICE6hEAALmiepQNEwUAACAhKAAAAAnVIwAAckX1KBsmCgAAQEJQAAAAEqpHAADki+ZRJkwUAACAhKAAAAAkVI8AAMgVux5lw0QBAABICAoAAEBC9QgAgFxRPcqGiQIAAJAQFAAAgITqEQAAuaJ6lA0TBQAAICEoAAAACdUjAAByRfUoGyYKAABAQlAAAAASqkcAAOSL5lEmTBQAAICEoAAAACRUjwAAyBW7HmXDRAEAAEgICgAAQEL1CACAXFE9yoaJAgAAkBAUAACAhOoRAAC5onqUDRMFAAAgISgAAAAJ1SMAAPJF8ygTJgoAAEBCUAAAgHpu7dq1MXny5OjTp0907tw5TjrppJg9e/YGz1+4cGGMHDkyDjrooDjooIPizDPPjPnz52/UNQUFAABypVAo1MuPT2LKlClx1113xbhx4+Luu++OQqEQQ4YMiaqqqvWef9ZZZ8W8efPilltuiVtuuSXmz58fp59++kZdU1AAAIB6rKqqKqZNmxbDhw+Pvn37RocOHWLSpEmxYMGCmD59enL+0qVLY8aMGTFkyJDo2LFjdOzYMU455ZR48cUXY/HixXW+rqAAAAD12KxZs2L58uXRo0ePmmPNmzePjh07xowZM5LzGzVqFE2aNIlf/vKXsWzZsli2bFn86le/ij333DO22267Ol/XrkcAAORKfX3Dtf79+3/k44899th6j6+7t2CXXXapdXznnXeOefPmJec3atQoLrvsshg7dmx07do1CoVC7LTTTnHHHXdESUnd5wQmCgAAUI+tWLEiIiJKS0trHW/UqFFUVlYm51dXV8fLL78cXbp0iZ/85Cdx2223RevWreOMM86IZcuW1fm6JgoAAPAp2NDE4OOUlZVFxAf3Kqz7c0REZWVlNG7cODn/oYceijvvvDN+//vfR9OmTSMi4oYbbogvfOELce+998YJJ5xQp+uaKAAAkCvF3t0o612P1lWOKioqah2vqKiI8vLy5Pznnnsu2rZtWxMSIiK22267aNu2bbz++ut1vq6gAAAA9ViHDh2iadOm8fTTT9ccW7p0acycOTO6du2anL/LLrvE7Nmza9WSVqxYEXPmzIk99tijztcVFAAAoB4rLS2NwYMHx8SJE+Oxxx6LWbNmxVlnnRXl5eUxYMCAWLNmTSxcuDBWrlwZERFHHXVURER85zvfiVmzZtWcX1paGkcffXSdrysoAACQK8WuGG2ON1wbMWJEDBw4MC666KI49thjo0GDBjF16tQoLS2NefPmRe/evePhhx+OiA92Q7rzzjujuro6TjjhhPjWt74VDRs2jJ/+9KfRvHnzur+O1dXV1Z9o1ZvBETem+8HC5rBD87KPPwkyMPO1RcVeAluJs/9rr2Ivga3ENz63a7GXsEG7Dr2v2EtYr7k/qvtv8+sDEwUAACBhe1QAAPKlfr7f2hbHRAEAAEgICgAAQEL1CACAXPmkOwzxARMFAAAgISgAAAAJ1SMAAHJF9SgbJgoAAEBCUAAAABKqRwAA5IrqUTZMFAAAgISgAAAAJFSPAADIF82jTJgoAAAACUEBAABIqB4BAJArdj3KhokCAACQEBQAAICE6hEAALmiepQNEwUAACAhKAAAAAnVIwAAckX1KBsmCgAAQEJQAAAAEqpHAADkiupRNkwUAACAhKAAAAAkVI8AAMgXzaNMmCgAAAAJQQEAAEjUy+rRO0tWFnsJbCV+dlK3Yi+BrcTuQ39W7CWwlTh8377FXgIUnV2PsmGiAAAAJAQFAAAgUS+rRwAAsKlUj7JhogAAACQEBQAAIKF6BABArmgeZcNEAQAASAgKAABAQvUIAIBcsetRNkwUAACAhKAAAAAkVI8AAMgVzaNsmCgAAAAJQQEAAEioHgEAkCt2PcqGiQIAAJAQFAAAgITqEQAAuaJ5lA0TBQAAICEoAAAACdUjAABypaRE9ygLJgoAAEBCUAAAABKqRwAA5Ipdj7JhogAAACQEBQAAIKF6BABArhR0jzJhogAAACQEBQAAIKF6BABArmgeZcNEAQAASAgKAABAQvUIAIBcsetRNkwUAACAhKAAAAAkVI8AAMgV1aNsmCgAAAAJQQEAAEioHgEAkCuaR9kwUQAAABKCAgAAkFA9AgAgV+x6lA0TBQAAICEoAAAACdUjAAByRfMoGyYKAABAQlAAAAASqkcAAOSKXY+yYaIAAAAkBAUAACChegQAQK5oHmXDRAEAAEgICgAAQEL1CACAXLHrUTZMFAAAgISgAAAAJFSPAADIFc2jbJgoAAAACUEBAABIqB4BAJArdj3KhokCAACQEBQAAICE6hEAALmieZQNEwUAACAhKAAAAAnVIwAAcsWuR9kwUQAAABKCAgAAkFA9AgAgVzSPsmGiAAAAJAQFAAAgoXoEAECu2PUoGyYKAABAQlAAAAASggIAAJBwjwIAALniFoVsmCgAAAAJQQEAAEioHgEAkCu2R82GiQIAAJAQFAAAgITqEQAAuaJ6lA0TBQAAICEoAAAACdUjAAByRfMoGyYKAABAQlAAAAASqkcAAOSKXY+yYaIAAAAkBAUAACAhKOREl922i5H92xd7GQCZ6bX3TjH+uC7FXgawBSoU6ufHlkZQAAAAEoICAACQsOsRAAC5YtejbJgoAAAACUEBAABIbFT16Pjjj6/zKOf222/fpAUBAMAnoXmUjY0KCj179oxrr7022rVrF/vvv//mWhMAAFBkGxUUTj/99GjSpElMnjw5fvSjH0WbNm0217oAAIAi2uh7FE488cQ44IAD4uqrr94MywEAgE+mpFColx9bmk26mfmyyy6Lww47LOu1sAl6tmsRDRvU/hev2x7bR5OGDYq0IoBP5tD9d4nSbWr/76lvx1axbZkdvQE+TZsUFFq1ahVf+MIXsl4Lm6C0QUlMO75L7N2qaWzbqEF8/8h9ou9nd4z3V60p9tIANkmjbUpi+ugB0XmPFtG8ScO45fRecdgBrWP5ytXFXhrAVsWvZ7Zwf3jlndimQUlc8tW9o6RQiIf+Pj8mTv9XsZcFsMke+utb0XCbkrhhSI8oKSnET//8Wpx7x1+LvSxgC7IFtnzqJUEhBx6btTD227VZ9GzXMiY++mqxlwPwif3ymTejW/sd49D9yuM8IQGgKASFnLj5idnx4N8XRNXqtcVeCkAmrvjlP+LOP/07VqpSAhSFoJATyyrXxL8WLi/2MgAys3TFqnhxzpJiLwPYAtX1DYL5aJt0MzMAAJBvggIAAJBQPQIAIFdKNI8yYaIAAAAkBAUAAKjn1q5dG5MnT44+ffpE586d46STTorZs2dv8PxVq1bFlVdeGX369InPfe5zMXjw4HjppZc26pqCAgAAuVIoFOrlxycxZcqUuOuuu2LcuHFx9913R6FQiCFDhkRVVdV6z7/kkkvinnvuiUsvvTTuvffe2H777WPIkCHx3nvv1fmaggIAANRjVVVVMW3atBg+fHj07ds3OnToEJMmTYoFCxbE9OnTk/PffPPNuOeee2L8+PFxyCGHRPv27eP73/9+lJaWxj/+8Y86X1dQAACAemzWrFmxfPny6NGjR82x5s2bR8eOHWPGjBnJ+X/+85+jefPmcfDBB9c6/3e/+1307Nmzzte16xEAALlSX99vrX///h/5+GOPPbbe4/Pnz4+IiF122aXW8Z133jnmzZuXnP/666/HbrvtFo888kjceOONsWDBgujYsWN897vfjfbt29d5vSYKAABQj61YsSIiIkpLS2sdb9SoUVRWVibnL1u2LN54442YMmVKjBw5Mn74wx/GNttsE8cdd1y88847db6uiQIAAHwKNjQx+DhlZWUR8cG9Cuv+HBFRWVkZjRs3Ts5v2LBhvPfeezFp0qSaCcKkSZOib9++8Ytf/CJOPvnkOl3XRAEAgFwp1NN/NtW6ylFFRUWt4xUVFVFeXp6cX15eHttss02tmlFZWVnstttuMWfOnDpfV1AAAIB6rEOHDtG0adN4+umna44tXbo0Zs6cGV27dk3O79q1a6xevTr+/ve/1xxbuXJlvPnmm7HHHnvU+bqqRwAAUI+VlpbG4MGDY+LEidGyZcto3bp1TJgwIcrLy2PAgAGxZs2aWLRoUTRr1izKysqia9eu0atXrzjvvPNi7Nixsf3228fkyZOjQYMGceSRR9b5uiYKAADkSkmhfn58EiNGjIiBAwfGRRddFMcee2w0aNAgpk6dGqWlpTFv3rzo3bt3PPzwwzXnX3vttdG9e/cYNmxYDBw4MJYtWxa33357tGzZss7XLFRXV1d/smVn7/MT/lTsJbCVeOysPsVeAluJ3Yf+rNhLYCvxxo/+u9hLYCtRVo97KUfcmL63QH1w/yndir2EjWKiAAAAJOpxFgQAgI1XqK/vuLaFMVEAAAASggIAAJBQPQIAIFc0j7JhogAAACQEBQAAIKF6BABArpToHmXCRAEAAEgICgAAQEL1CACAXNE8yoaJAgAAkBAUAACAhOoRAAC5UtA9yoSJAgAAkBAUAACAhOoRAAC5onmUDRMFAAAgISgAAAAJ1SMAAHKlRPcoEyYKAABAQlAAAAASqkcAAOSK4lE2TBQAAICEoAAAACRUjwAAyJWCXY8yYaIAAAAkBAUAACChegQAQK6UaB5lwkQBAABICAoAAEBC9QgAgFyx61E2TBQAAICEoAAAACRUjwAAyBXNo2yYKAAAAAlBAQAASKgeAQCQK3Y9yoaJAgAAkBAUAACAhOoRAAC5UqJ5lAkTBQAAICEoAAAACdUjAAByxa5H2TBRAAAAEoICAACQUD0CACBXFI+yYaIAAAAkBAUAACChegQAQK6U2PUoEyYKAABAQlAAAAASqkcAAOSK5lE2TBQAAICEoAAAACRUjwAAyJWC7lEmTBQAAICEoAAAACRUjwAAyBXNo2yYKAAAAAlBAQAASKgeAQCQKyW6R5kwUQAAABKCAgAAkFA9AgAgVzSPsmGiAAAAJAQFAAAgoXoEAECuFHSPMmGiAAAAJAQFAAAgUS+rR2+//X6xl8BWYvdTflbsJbCVeG/B/GIvAWCr4Tfh2fA6AgAACUEBAABI1MvqEQAAbCq7HmXDRAEAAEgICgAAQEL1CACAXCnRPMqEiQIAAJAQFAAAgITqEQAAuaJ6lA0TBQAAICEoAAAACdUjAAByxRuuZcNEAQAASAgKAABAQvUIAIBcsetRNkwUAACAhKAAAAAkVI8AAMgVmx5lw0QBAABICAoAAEBC9QgAgFwp0T3KhIkCAACQEBQAAICE6hEAALniN+HZ8DoCAAAJQQEAAEioHgEAkCs2PcqGiQIAAJAQFAAAgITqEQAAueIN17JhogAAACQEBQAAIKF6BABArmgeZcNEAQAASAgKAABAQvUIAIBcKVE9yoSJAgAAkBAUAACAhOoRAAC54g3XsmGiAAAAJAQFAAAgoXoEAECuaB5lw0QBAABICAoAAEBC9QgAgFzxhmvZMFEAAAASggIAAJBQPQIAIFcKoXuUBRMFAAAgISgAAAAJ1SMAAHLFrkfZMFEAAAASggIAAJBQPQIAIFdUj7JhogAAACQEBQAAIKF6BABArhQKukdZMFEAAAASggIAAJBQPQIAIFfsepQNEwUAACAhKAAAAAnVIwAAcsWmR9kwUQAAABKCAgAAkFA9AgAgV0p0jzJhogAAACQEBQAAIKF6BABArnjDtWyYKAAAAAlBAQAASAgKAADkSqFQPz8+ibVr18bkyZOjT58+0blz5zjppJNi9uzZdXruAw88EHvvvXfMmTNno64pKAAAQD03ZcqUuOuuu2LcuHFx9913R6FQiCFDhkRVVdVHPu+tt96KMWPGbNI1BQUAAKjHqqqqYtq0aTF8+PDo27dvdOjQISZNmhQLFiyI6dOnb/B5a9eujXPOOSc6deq0SdcVFAAAyJWSKNTLj001a9asWL58efTo0aPmWPPmzaNjx44xY8aMDT7vhhtuiFWrVsXQoUM36bq2RwUAgE9B//79P/Lxxx57bL3H58+fHxERu+yyS63jO++8c8ybN2+9z/nb3/4W06ZNi3vuuScWLFiwCas1UQAAgHptxYoVERFRWlpa63ijRo2isrIyOf/999+Ps88+O84+++zYc889N/m6JgoAAOTKJ91haHPZ0MTg45SVlUXEB/cqrPtzRERlZWU0btw4OX/cuHGx5557xjHHHLNpC/3/BAUAAKjH1lWOKioqYvfdd685XlFRER06dEjOv/fee6O0tDS6dOkSERFr1qyJiIivfvWrccQRR8TYsWPrdF1BAQAA6rEOHTpE06ZN4+mnn64JCkuXLo2ZM2fG4MGDk/MfeeSRWn9/4YUX4pxzzokbb7wx2rdvX+frCgoAAORKST2tHm2q0tLSGDx4cEycODFatmwZrVu3jgkTJkR5eXkMGDAg1qxZE4sWLYpmzZpFWVlZ7LHHHrWev+5m6F133TV22GGHOl/XzcwAAFDPjRgxIgYOHBgXXXRRHHvssdGgQYOYOnVqlJaWxrx586J3797x8MMPZ3rNQnV1dXWmnzEDe5/322Ivga3E4oVLir0EthLvLZhf7CWwlVj8qxHFXgJbibJ63Eu54anXi72E9Tq1557FXsJGqcffYgAA2Hgl9XXboy2M6hEAAJAQFAAAgITqEQAAuaJ5lA0TBQAAICEoAAAACUEB2Ci99t4pxg/qUuxlsBXos1/rmHRq32IvA9gClRQK9fJjSyMoAAAACUEBAABI2PUIAIBc2QJbPvVSnScKr732Wlx77bUxbty4+MMf/pA8vmzZsjj//PMzXRyfzIF7bl/sJQAAsIWqU1B47rnn4mtf+1o8+OCD8cc//jFOPfXUGD58eFRVVdWcs3LlyvjlL3+5udbJJui3z84xpG/bYi8DAIAtUJ2CwpVXXhkDBw6M3/72t/HII4/EVVddFU888USceuqpsWrVqs29RjbR9Y+9Gl/v1jouPLxDNGxgBgcAbB1K6unHlqZO9yi8/PLL8f3vf7/m7//1X/8VO++8c5x88slx7rnnxqRJkzbbAvk//TvuFN/50l4b9ZymZdvEN3vvEQe2bRFHT35qM60MAIC8qVNQaNq0aSxevDj23HPPmmMHHnhgTJgwIUaMGBHjx4+PIUOGbK418v89NnNhPDZzYZ3Pb1BSiNuGdI0X5yyN79334mZcGQAAeVOnKUjfvn1j7Nix8cILL9SqGh166KFxwQUXxG233RZjx47dbItk03zz87vHvxcuj1Nv+2tULK0s9nIAAD4VhUKhXn5saeoUFEaNGhUtWrSIY445Jp56qnZ9ZfDgwTF69Oj43e9+t1kWyKZbtHxVjL5vZlRXF3sl5MGh++8SpdvU/k9G346tYtsyuyyTrS932zNKt2lQ61i/z+0WTRs3LNKKALZOdfo//HbbbRfTpk2LN954I1q0aJE8ftxxx0XPnj3jkUceyXyBbLpf/XVusZdAjjTapiSmjx4Qdz3xWjRv3DBuOaNXLFy6Mv4wc0Gxl0bONGrYIJ685pj48aMzo/m2jeKuC78SCxa/H7/73zeLvTSArcpG/Spw99133+Bjbdu2jaFDh37iBQH100N/fSsablMSN5zSI0pKCvHTP78W5/74r8VeFjn0qydfjdJtSuLWc74cJSWFuH36zDhzyuPFXhawBdnySj71k84AUGe/fObN6PaZHePQ/crjPCGBzejnf3wleuyzS3yp655x5pTfF3s5AFslQQHYKFf84h9x55/+HStXrSn2Usi5sXf8JW59ZGasrPLvGkAxCArARlm6YlW8+OaSYi+DrcCS5VXx99feLvYygC1QyRa4w1B9tCW+SRwAALCZCQoAAEBC9QgAgFxRPMqGiQIAAJAQFAAAgITqEQAAuWLTo2yYKAAAAAlBAQAASKgeAQCQKwXdo0yYKAAAAAlBAQAASKgeAQCQK34Tng2vIwAAkBAUAACAhOoRAAC5YtejbJgoAAAACUEBAABIqB4BAJArikfZMFEAAAASggIAAJBQPQIAIFfsepQNEwUAACAhKAAAAAnVIwAAcsVvwrPhdQQAABKCAgAAkFA9AgAgV+x6lA0TBQAAICEoAAAACdUjAAByRfEoGyYKAABAQlAAAAASqkcAAOSKTY+yYaIAAAAkBAUAACChegQAQK6U2PcoEyYKAABAQlAAAAASqkcAAOSKXY+yYaIAAAAkBAUAACChegQAQK4U7HqUCRMFAAAgISgAAAAJ1SMAAHLFrkfZMFEAAAASggIAAJBQPQIAIFdK7HqUCRMFAAAgISgAAAAJ1SMAAHLFrkfZMFEAAAASggIAAJBQPQIAIFdUj7JhogAAACQEBQAAIKF6BABArhS84VomTBQAAICEoAAAACRUjwAAyJUSzaNMmCgAAAAJQQEAAEioHgEAkCt2PcqGiQIAAJAQFAAAgITqEQAAuVLQPMqEiQIAAJAQFAAAgITqEQAAuWLXo2yYKAAAAAlBAQAASKgeAQCQKyWaR5kwUQAAABKCAgAAkFA9AgAgV+x6lA0TBQAAICEoAAAACdUjAABypaB5lAkTBQAAICEoAAAACdUjAAByRfMoGyYKAABAQlAAAAASqkcAAORKiW2PMmGiAAAAJAQFAAAgUS+rRy9c9qViL4GtRIsjJxd7CWwt5v6z2CsA2GooHmXDRAEAAEgICgAAQKJeVo8AAGCT6R5lwkQBAABICAoAAEBC9QgAgFwp6B5lwkQBAABICAoAAEBC9QgAgFwpaB5lwkQBAABICAoAAEBC9QgAgFzRPMqGiQIAAJAQFAAAgITqEQAA+aJ7lAkTBQAAICEoAAAACdUjAABypaB7lAkTBQAAICEoAAAACdUjAABypaB5lAkTBQAAICEoAAAACdUjAAByRfMoGyYKAABAQlAAAAASqkcAAOSL7lEmTBQAAICEoAAAACRUjwAAyJWC7lEmTBQAAICEoAAAACRUjwAAyJWC5lEmTBQAAKCeW7t2bUyePDn69OkTnTt3jpNOOilmz569wfNfeeWVOOWUU+Kggw6Knj17xogRI2Lu3LkbdU1BAQAA6rkpU6bEXXfdFePGjYu77747CoVCDBkyJKqqqpJzFy9eHN/61rdi2223jTvuuCNuuummWLx4cZx88slRWVlZ52sKCgAA5Eqhnn5sqqqqqpg2bVoMHz48+vbtGx06dIhJkybFggULYvr06cn5jz76aKxYsSIuv/zy2GuvvWLfffeNCRMmxKuvvhp//etf63xdQQEAAOqxWbNmxfLly6NHjx41x5o3bx4dO3aMGTNmJOf37Nkzrr/++mjUqFHy2JIlS+p8XTczAwDAp6B///4f+fhjjz223uPz58+PiIhddtml1vGdd9455s2bl5zfpk2baNOmTa1jP/rRj6JRo0bRrVu3Oq/XRAEAgHwpdsco4+7RihUrIiKitLS01vFGjRrV6Z6D22+/Pe68884YOXJk7LDDDnW+rokCAAB8CjY0Mfg4ZWVlEfHBvQrr/hwRUVlZGY0bN97g86qrq+Oaa66JH/7whzF06NA48cQTN+q6JgoAAFCPrascVVRU1DpeUVER5eXl633OqlWr4pxzzokbbrghzj333Bg5cuRGX1dQAAAgVwr19J9N1aFDh2jatGk8/fTTNceWLl0aM2fOjK5du673Oeeee2785je/iSuvvDK+/e1vb9J1VY8AAKAeKy0tjcGDB8fEiROjZcuW0bp165gwYUKUl5fHgAEDYs2aNbFo0aJo1qxZlJWVxX333RcPP/xwnHvuudG9e/dYuHBhzedad05dmCgAAEA9N2LEiBg4cGBcdNFFceyxx0aDBg1i6tSpUVpaGvPmzYvevXvHww8/HBERDz74YERE/OAHP4jevXvX+lh3Tl0UqqurqzfLV/MJrFxd7BWwtWhx5ORiL4Gtxdx/FnsFbCUWz7iu2EtgK1FWj3spf5+zrNhLWK/92jQt9hI2iokCAACQEBQAAIBEPR4aAQDAxvsE723Gh5goAAAACUEBAABIqB4BAJAvukeZMFEAAAASggIAAJBQPQIAIFcKukeZMFEAAAASggIAAJBQPQIAIFcKmkeZMFEAAAASggIAAJBQPQIAIFc0j7JhogAAACQEBQAAIKF6BABAvugeZcJEAQAASAgKAABAQvUIAIBcKegeZcJEAQAASAgKAABAQvUIAIBcKWgeZcJEAQAASAgKAABAQvUIAIBc0TzKhokCAACQEBQAAICEoAAAACTcowAAQL64SSETJgoAAEBCUAAAABKqRwAA5EpB9ygTJgoAAEBCUAAAABKqRwAA5EpB8ygTJgoAAEBCUAAAABKqRwAA5IrmUTZMFAAAgISgAAAAJFSPAADIF92jTJgoAAAACUEBAABIqB4BAJArBd2jTJgoAAAACUEBAABIbFT1qLKyMl555ZX4zGc+E2VlZfHSSy/FHXfcEQsWLIi99torTjjhhCgvL99cawXqqc932jWeeHFusZfBVuDzXdrHE8+/WuxlAPVcQfMoE3WeKLz66qtx6KGHxsCBA+MrX/lKPPnkk3HsscfGCy+8ENtuu208+uijceSRR8arr/oPOGxtvtK9bYwaeGCxl8FW4CsH7xujTjy02MsA2CrUOSj84Ac/iC5dusQvf/nLOPDAA+O0006Lww8/PB544IG45ppr4te//nV8/vOfj/Hjx2/O9QL10Pd/+kyc8MWOMfGUg6PhNhqNbD7fv/HXccJRvWLiOV+Phts0KPZyAHKtUF1dXV2XE7t06RL33ntvtGvXLt5+++3o3bt33HfffdGxY8eac/75z3/G//zP/8Tzzz//iRa1cvUnejrUWYsjJxd7CfXSV3u0i0uO77lRz9lhu7Iob7FtPP+viuh15l2baWVbsLn/LPYK6qWvHrJfXHLG4Rv1nB22bxrlOzaP5196M3odd8VmWtmWa/GM64q9BLYSZfV478zX315Z7CWs1547lhV7CRulzt/isrKyWLnygxd9xx13jP/+7/+ORo0a1Tpn6dKl0axZs2xXCHzqHvzLv+PBv/y7zuc3KCnEb8YfHc//qyKGXfu7zbgy8ubBx/8eDz7+9zqf36BBSfzmxhHx/EtvxLBLf7oZVwZAnTsCvXv3jksvvbTmHoSxY8dG+/btIyKiuro6nn766Rg9enQceqjuKGxthh35uXh5zuL4+pgHYu47y4u9HHJs2HGHxMuvLYivn/mjmLtwSbGXA5BrdQ4K559/fqxZsyamTJmSPPbwww/HCSecEK1bt46RI0dmukCg/lu4ZEUMu/Z3UbciI2y6hYuXxbBxP406tmaBrVWhnn5sYep8j8I67777bmy//fa1ji1atCgqKiqiQ4cOmSzKPQp8WtyjwKfGPQp8StyjwKelXt+j8E49vUdhh5zeo7DOf4aEiIiWLVtGy5Yts1gPAABQD9TjLAgAABuvsCX2fOohG54DAAAJQQEAAEioHgEAkCsFzaNMmCgAAAAJQQEAAEioHgEAkCuaR9kwUQAAABKCAgAAkFA9AgAgV+x6lA0TBQAAICEoAAAACdUjAAByRvcoCyYKAABAQlAAAAASqkcAAOSKXY+yYaIAAAAkBAUAACChegQAQK5oHmXDRAEAAEgICgAAQEL1CACAXLHrUTZMFAAAgISgAAAAJFSPAADIlYJ9jzJhogAAACQEBQAAIKF6BABAvmgeZcJEAQAASAgKAABAQvUIAIBc0TzKhokCAACQEBQAAICE6hEAALlS0D3KhIkCAACQEBQAAICE6hEAALlSsO9RJkwUAACAhKAAAAAkVI8AAMgXzaNMmCgAAAAJQQEAAEioHgEAkCuaR9kwUQAAABKCAgAAkFA9AgAgVwq6R5kwUQAAABKCAgAAkFA9AgAgVwr2PcqEiQIAAJAQFAAAgITqEQAAuWLXo2yYKAAAAAlBAQAASAgKAABAQlAAAAASggIAAJCw6xEAALli16NsmCgAAAAJQQEAAEioHgEAkCuF0D3KgokCAACQEBQAAICE6hEAALli16NsmCgAAAAJQQEAAEioHgEAkCuaR9kwUQAAABKCAgAAkFA9AgAgX3SPMmGiAAAAJAQFAAAgoXoEAECuFHSPMmGiAAAAJAQFAAAgoXoEAECuFDSPMmGiAAAAJAQFAAAgoXoEAECuaB5lw0QBAABICAoAAEBC9QgAgHzRPcqEiQIAAJAQFAAAgITqEQAAuVLQPcqEiQIAANRza9eujcmTJ0efPn2ic+fOcdJJJ8Xs2bM3eP7ixYtj1KhR0a1bt+jWrVt873vfi/fff3+jrikoAABAPTdlypS46667Yty4cXH33XdHoVCIIUOGRFVV1XrPHzFiRLz55ptx6623xuTJk+OJJ56IMWPGbNQ1BQUAAHKlUKifH5uqqqoqpk2bFsOHD4++fftGhw4dYtKkSbFgwYKYPn16cv7zzz8fzzzzTIwfPz46deoUPXv2jLFjx8avfvWrWLBgQZ2vKygAAEA9NmvWrFi+fHn06NGj5ljz5s2jY8eOMWPGjOT8Z599Nnbaaado3759zbHu3btHoVCI5557rs7XdTMzAAB8Cvr37/+Rjz/22GPrPT5//vyIiNhll11qHd95551j3rx5yfkLFixIzi0tLY3tt99+vedvSL0MCmX1clXk0YqHRhR7CQBAxvL2s+SKFSsi4oMf9j+sUaNGsWTJkvWe/5/nrju/srKyztfN2csIAAD104YmBh+nrKwsIj64V2HdnyMiKisro3Hjxus9f303OVdWVkaTJk3qfF33KAAAQD22rkZUUVFR63hFRUWUl5cn55eXlyfnVlVVxbvvvhutWrWq83UFBQAAqMc6dOgQTZs2jaeffrrm2NKlS2PmzJnRtWvX5Pxu3brF/Pnza73PwrrnHnDAAXW+ruoRAADUY6WlpTF48OCYOHFitGzZMlq3bh0TJkyI8vLyGDBgQKxZsyYWLVoUzZo1i7KysujcuXMccMABcdZZZ8Ull1wS77//flx88cVx1FFHbdREoVBdXV29Gb8uAADgE1qzZk1cddVVcd9998XKlSujW7duMXr06GjTpk3MmTMn+vfvH+PHj4+jjz46IiLeeeedGDNmTPzpT3+KRo0axZe//OU4//zzo1GjRnW+pqAAAAAk3KMAAAAkBAUAACAhKAAAAAlBAQAASAgKAABAQlAAAAASggIAAJAQFLZwa9eujcmTJ0efPn2ic+fOcdJJJ9V6u27YHKZMmRLHH398sZdBTr377rsxevToOPjgg+OAAw6IY489Np599tliL4sceuedd+Kcc86JHj16RJcuXeKUU06Jf/3rX8VeFtQbgsIWbsqUKXHXXXfFuHHj4u67745CoRBDhgyJqqqqYi+NnLr11ltj8uTJxV4GOTZy5Mh44YUX4qqrrop77rknOnXqFN/+9rfj1VdfLfbSyJnTTjst3nzzzbjpppvinnvuibKysjjxxBNjxYoVxV4a1AuCwhasqqoqpk2bFsOHD4++fftGhw4dYtKkSbFgwYKYPn16sZdHzixYsCBOPvnkuOaaa6Jt27bFXg45NXv27HjiiSfi4osvjq5du0a7du3iwgsvjFatWsWDDz5Y7OWRI4sXL442bdrEpZdeGvvtt1+0b98+Tj/99Fi4cGG88sorxV4e1AuCwhZs1qxZsXz58ujRo0fNsebNm0fHjh1jxowZRVwZefTiiy/GdtttF/fff3907ty52Mshp1q0aBE33nhj7LvvvjXHCoVCVFdXx5IlS4q4MvKmRYsWcdVVV8Vee+0VERFvv/12TJ06NcrLy+Mzn/lMkVcH9cM2xV4Am27+/PkREbHLLrvUOr7zzjvHvHnzirEkcqxfv37Rr1+/Yi+DnGvevHn07du31rFf//rX8cYbb0Tv3r2LtCry7nvf+1787Gc/i9LS0vjhD38YTZo0KfaSoF4wUdiCretQlpaW1jreqFGjqKysLMaSADL13HPPxQUXXBD9+/cXVNlsTjjhhLj33nvjiCOOiDPOOCNefPHFYi8J6gVBYQtWVlYWEZHcuFxZWRmNGzcuxpIAMvPoo4/Gt7/97dh///3jqquuKvZyyLHPfOYzse+++8all14abdq0iTvuuKPYS4J6QVDYgq2rHFVUVNQ6XlFREeXl5cVYEkAm7rjjjhg+fHgcfPDBcdNNN9X8YgSy8s4778SDDz4Ya9asqTlWUlIS7du3T/6/ClsrQWEL1qFDh2jatGk8/fTTNceWLl0aM2fOjK5duxZxZQCb7s4774xLL700Bg0aFFdffXVSr4QsVFRUxKhRo+KZZ56pObZq1aqYOXNmtG/fvogrg/rDzcxbsNLS0hg8eHBMnDgxWrZsGa1bt44JEyZEeXl5DBgwoNjLA9hor732Wnz/+9+PAQMGxNChQ+Odd96peaysrCyaNWtWxNWRJx06dIjevXvHmDFjYty4cdG8efO44YYbYunSpXHiiScWe3lQLwgKW7gRI0bE6tWr46KLLoqVK1dGt27dYurUqX4DB2yRfvvb38aqVati+vTpyfvBfO1rX4vLL7+8SCsjbwqFQlx99dVx5ZVXxne+85147733omvXrvGTn/wkdt1112IvD+qFQnV1dXWxFwEAANQv7lEAAAASggIAAJAQFAAAgISgAAAAJAQFAAAgISgAAAAJQQEAAEgICgAAQEJQAAAAEoICAACQEBQAAIDE/wM4ps0EB27JlgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_q_values_map(default_val_table, env, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32182529",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.9.18"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}