project_summary.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project Summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import time\n",
    "from datetime import datetime\n",
    "\n",
    "from game import Game, Player\n",
    "from utils import investigate_game\n",
    "from utils.investigate_game import InvestigateGame\n",
    "from players.random_player import RandomPlayer\n",
    "from players.min_max import MinMaxPlayer, AlphaBetaMinMaxPlayer\n",
    "from players.monte_carlo_rl import MonteCarloRLPlayer\n",
    "from players.monte_carlo_tree_search import MCTSPlayer\n",
    "from players.human_player import HumanPlayer\n",
    "\n",
    "import sys\n",
    "\n",
    "# needed to load Seralized Monte Carlo RL Player\n",
    "sys.modules['investigate_game'] = investigate_game"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_training_stats(\n",
    "    rewards: list, state_value_dict_size: int, step_size: int, switch_ratio: int | None = None\n",
    ") -> None:\n",
    "    \"\"\"\n",
    "    Given a training list of rewards and the size of the player's State-Value dictionary,\n",
    "    this function plots the averages of the rewards using a given step size.\n",
    "\n",
    "    Args:\n",
    "        rewards: the rewards achieved during training time;\n",
    "        state_value_dict_size: the length of the State-Value dictionary of the player;\n",
    "        step: the step size to be used to plot an average value;\n",
    "        switch_ratio: define the moment in which minmax started playing-\n",
    "\n",
    "    Returns:\n",
    "        None.\n",
    "    \"\"\"\n",
    "\n",
    "    # https://stackoverflow.com/questions/15956309/averaging-over-every-n-elements-of-a-numpy-array\n",
    "    # compute the averages\n",
    "    averages = np.mean(np.array(rewards).reshape(-1, step_size), axis=1)\n",
    "\n",
    "    # define the width and height of the figure in inches\n",
    "    plt.figure(figsize=(10, 5))\n",
    "    # plot the averages\n",
    "    plt.plot(averages, color='red', marker='o', linestyle='dashed', label='Training')\n",
    "    # if minmax played\n",
    "    if switch_ratio is not None:\n",
    "        # compute the exact moment\n",
    "        switch_moment = int(len(rewards) / step_size * switch_ratio)\n",
    "        # print a vertical line at the moment minmax started playing\n",
    "        plt.axvline(x=switch_moment, color='green', label='MinMax Starts Playing')\n",
    "    # specify the title\n",
    "    plt.title('Training Summary')\n",
    "    # specify the x-axis label\n",
    "    plt.xlabel('# of the step')\n",
    "    # specify the y-axis label\n",
    "    plt.ylabel('Mean rewards value')\n",
    "    # show the legend\n",
    "    plt.legend()\n",
    "    # add information text\n",
    "    plt.text(\n",
    "        -0.3,\n",
    "        0.1,\n",
    "        f'{state_value_dict_size}',\n",
    "        color=\"white\",\n",
    "        bbox=dict(facecolor='steelblue', boxstyle='round,pad=0.3,rounding_size=0.2'),\n",
    "        ha='right',\n",
    "        va='bottom',\n",
    "    )\n",
    "    # show the plot\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monte Carlo Reinforcement learning player\n",
    "\n",
    "To train a Reinforcement Learning player based on a Monte Carlo technique, we used a method referred as [**Temporal Difference learning (TD)**](https://en.wikipedia.org/wiki/Temporal_difference_learning#Mathematical_formulation). In short, the training is performed in such a way that the _State-Value_ function is updated as follows:\n",
    "$$\n",
    "V(S_{t})\\leftarrow (1-\\alpha )V(S_{t})+\\underbrace {\\alpha } _{\\text{learning rate}}[\\overbrace {R_{t+1}+\\gamma V(S_{t+1})} ^{\\text{The TD target}}]\n",
    "$$\n",
    "where $S_{t}$ is the state at time $t$, $\\gamma$ is the discount rate and $R_{t+1}$ is the reward at time $t+1$."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "### Show the training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0EAAAHUCAYAAAD8ySMAAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8pXeV/AAAACXBIWXMAAA9hAAAPYQGoP6dpAACQjElEQVR4nO3deXhTZdoG8DuErnSBLtCWFMqqKAgCIouVsoiKIEzYZHFAHIEBhAJuKFLwExFHKCgiog64sQlR1FGUpUXQQZFdEUQtWykUirRsLTQ93x/vnGZPzsnSpO39u65eSU7OOXmTBj1Pn/d9Ho0kSRKIiIiIiIiqiRr+HgAREREREVFFYhBERERERETVCoMgIiIiIiKqVhgEERERERFRtcIgiIiIiIiIqhUGQUREREREVK0wCCIiIiIiomqFQRAREREREVUrDIKIiIiIiKhaYRBERBSgNBqNop/s7GyPXmfWrFnQaDRuHZudne2VMbjr119/xcMPP4zGjRsjNDQUcXFxaNu2LSZOnIiioiK/jImIiAKfRpIkyd+DICIiWzt37rR4/H//93/IysrC1q1bLbbfcsstiIqKcvt1Tp06hVOnTqFjx46qjy0qKsKhQ4c8HoM79u7diy5duqBFixZ4/PHHkZKSgvPnz2P//v1YvXo1Nm3ahJSUlAodExERVQ4MgoiIKolRo0Zh3bp1uHz5stP9rl69ivDw8Aoalf+MHDkS69evR15eHiIjI22elyTJ7QxXZVVdfvdERJ7idDgiokosLS0NLVu2xLfffovOnTsjPDwco0ePBgCsWbMGvXr1QmJiIsLCwtCiRQs888wzuHLlisU57E2HS0lJQZ8+fbBx40a0bdsWYWFhuPnmm/Hvf//bYj970+FGjRqFiIgI/P777+jduzciIiKQnJyMadOmoaSkxOL4U6dOYeDAgYiMjETt2rUxfPhw7Nq1CxqNBitWrHD63gsKChAVFYWIiAi7z5u/p5SUFIwaNcru55eWlmbzflauXImnn34aiYmJiIiIQN++fXH27FlcunQJY8aMQVxcHOLi4vDII4/YBKUajQYTJ07E8uXLcdNNNyEsLAzt27fHzp07IUkS/vWvf6FRo0aIiIhA9+7d8fvvv1scv2nTJvTr1w86nQ6hoaFo2rQpxo4di/Pnz1vsJ//e9uzZg4EDB6JOnTpo0qQJPvjgA2g0Gvz3v/+1eb8vvPACgoKCcPr0aaefLRFRVccgiIioksvLy8OIESMwbNgwfPnllxg/fjwA4OjRo+jduzfeffddbNy4Eenp6Vi7di369u2r6Lz79+/HtGnTMGXKFGzYsAG33XYbHn30UXz77bcuj71x4wYefPBB9OjRAxs2bMDo0aORmZmJefPmle9z5coVdOvWDVlZWZg3bx7Wrl2LevXqYciQIYrG16lTJ+Tl5WH48OHYtm0brl27pug4JZ599lnk5+djxYoVmD9/PrKzszF06FAMGDAA0dHRWLVqFZ566il88MEHePbZZ22O/+KLL/DOO+/g5ZdfxqpVq3Dp0iU88MADmDZtGr777jssXrwYy5Ytw6FDhzBgwACYT8r4448/0KlTJ7z55pv45ptvMHPmTPzwww+46667cOPGDZvX0uv1aNq0KT7++GMsXboUQ4YMQUJCAt544w2L/UpLS/HWW2/hb3/7G5KSkrz2WRERVUoSERFVCiNHjpRq1aplsa1r164SAGnLli1Ojy0rK5Nu3Lghbdu2TQIg7d+/v/y5jIwMyfp/Bw0bNpRCQ0Ol48ePl2+7du2aFBMTI40dO7Z8W1ZWlgRAysrKshgnAGnt2rUW5+zdu7d00003lT9+4403JADSV199ZbHf2LFjJQDS8uXLnb6n4uJiqX///hIACYCk1Wql22+/XXruueek/Px8m/czcuRIm3N07dpV6tq1q8376du3r8V+6enpEgBp0qRJFtv79+8vxcTEWGwDICUkJEiXL18u3/bpp59KAKQ2bdpIZWVl5dsXLlwoAZAOHDhg9z3Kv7fjx49LAKQNGzaUPyf/3mbOnGlzXEZGhhQcHCydPXu2fNuaNWskANK2bdvsvhYRUXXCTBARUSVXp04ddO/e3Wb7n3/+iWHDhiEhIQFarRZBQUHo2rUrAFFVzZU2bdqgQYMG5Y9DQ0PRvHlzHD9+3OWxGo3GJuN02223WRy7bds2REZG4r777rPYb+jQoS7PDwAhISH45JNPcOjQIWRmZuKhhx7CuXPnMGfOHLRo0QJHjhxRdB57+vTpY/G4RYsWAIAHHnjAZvuFCxdspsR169YNtWrVsjn+/vvvt5imJ283/1zy8/Mxbtw4JCcno2bNmggKCkLDhg0B2P+9DRgwwGbbP//5TwDA22+/Xb5t8eLFaNWqFe6++25Hb5uIqNqo6e8BEBGRZxITE222Xb58GampqQgNDcWLL76I5s2bIzw8HCdPnoRer1c0dSw2NtZmW0hIiKJjw8PDERoaanNscXFx+eOCggLUq1fP5lh725xp0aJFeTAhSRIWLlyIqVOn4vnnn8fatWtVnUsWExNj8Tg4ONjp9uLiYou1Se4cDwBlZWXo1asXTp8+jeeffx6tWrVCrVq1UFZWho4dO9r97O39/uVphW+99RaeeeYZ/PLLL9i+fTveeust12+eiKgaYBBERFTJ2auAtnXrVpw+fRrZ2dnl2R8AuHjxYgWOzLnY2Fj8+OOPNtvPnDnj9jk1Gg2mTJmCF154AT///HP59tDQUJuiDABw/vx5xMXFuf163vbzzz9j//79WLFiBUaOHFm+3bp4gjlHFfAmT56MDz74ABs2bMDGjRvLC08QERELIxARVUnyhXFISIjF9kDKBHTt2hWXLl3CV199ZbF99erVio7Py8uzu/306dMoKiqyWPyfkpKCAwcOWOz322+/eTRlzhe8+Xtr164dOnfujHnz5uGjjz7CqFGjLKboERFVZ8wEERFVQZ07d0adOnUwbtw4ZGRkICgoCB999BH279/v76GVGzlyJDIzMzFixAi8+OKLaNq0Kb766it8/fXXAIAaNZz/nW7MmDG4ePEiBgwYgJYtW0Kr1eLw4cPIzMxEjRo18PTTT5fv+/DDD2PEiBEYP348BgwYgOPHj+OVV15BfHy8T9+jWjfffDOaNGmCZ555BpIkISYmBp9//jk2bdrk1vkmT56MIUOGQKPRlFcNJCIiZoKIiKqk2NhY/Oc//0F4eDhGjBiB0aNHIyIiAmvWrPH30MrVqlULW7duRVpaGp566ikMGDAAJ06cwJIlSwAAtWvXdnr8448/jubNm+Ptt9/GwIED0atXL/zf//0fWrVqhe3bt+Oee+4p33fYsGF45ZVX8PXXX6NPnz5488038eabb6J58+a+fIuqBQUF4fPPP0fz5s0xduxYDB06FPn5+di8ebNb5+vfvz9CQkJw7733olmzZl4eLRFR5aWRJLPmBERERH720ksvYcaMGThx4gR0Op2/h1Opff7553jwwQfxn//8B7179/b3cIiIAgaDICIi8pvFixcDENPAbty4ga1bt+K1117DkCFD8P777/t5dJXXoUOHcPz4cUyePBm1atXCnj17HBZQICKqjrgmiIiI/CY8PByZmZk4duwYSkpK0KBBAzz99NOYMWOGv4dWqY0fPx7fffcd2rZti/fee48BEBGRFWaCiIiIiIioWmFhBCIiIiIiqlYYBBERERERUbXCIIiIiIiIiKqVSl0YoaysDKdPn0ZkZCQXfRIRERERVWOSJOHSpUtISkpy2XC7UgdBp0+fRnJysr+HQUREREREAeLkyZMu+8xV6iAoMjISgHijUVFRfh4NERERERH5S1FREZKTk8tjBGf8GgSVlpZi1qxZ+Oijj3DmzBkkJiZi1KhRmDFjhssUFoDyKXBRUVEMgoiIiIiISNEyGb8GQfPmzcPSpUvx3nvv4dZbb8VPP/2ERx55BNHR0Zg8ebI/h0ZERERERFWUX4Og//73v+jXrx8eeOABAEBKSgpWrVqFn376yZ/DIiIiIiKiKsyvJbLvuusubNmyBb/99hsAYP/+/dixYwd69+5td/+SkhIUFRVZ/BAREREREanh10zQ008/jcLCQtx8883QarUwGo2YM2cOhg4danf/uXPnYvbs2apeQ5IklJaWwmg0emPI5CVarRY1a9ZkaXMiIiIiqnB+DYLWrFmDDz/8ECtXrsStt96Kffv2IT09HUlJSRg5cqTN/tOnT8fUqVPLH8sVIBy5fv068vLycPXqVZ+MnzwTHh6OxMREBAcH+3soRERERFSNaCRJkvz14snJyXjmmWcwYcKE8m0vvvgiPvzwQxw+fNjl8UVFRYiOjkZhYaFNdbiysjIcPXoUWq0W8fHxCA4OZtYhQEiShOvXr+PcuXMwGo1o1qyZomqARERERESOOIsNrPk1E3T16lWbi1+tVouysjKPz339+nWUlZUhOTkZ4eHhHp+PvCssLAxBQUE4fvw4rl+/jtDQUH8PiYiIiIiqCb8GQX379sWcOXPQoEED3Hrrrdi7dy8WLFiA0aNHe+01mGEIXPzdEBEREZE/+DUIev311/H8889j/PjxyM/PR1JSEsaOHYuZM2f6c1hERERERFSF+TUIioyMxMKFC7Fw4UJ/DoOIiIiIApXRCGzfDuTlAYmJQGoqoNX6e1RUyXE+khJGI5CdDaxaJW4rYbnttLQ0pKenK97/2LFj0Gg02Ldvn8/GREREROSUwQCkpADdugHDhonblBSxncgDfs0EVQoGAzB5MnDqlGmbTgcsWgTo9V5/OVcV7EaOHIkVK1aoPq/BYEBQUJDi/ZOTk5GXl4e4uDjVr0VERETkMYMBGDgQsC5knJsrtq9b55NrMaoeGAQ544d/fHl5eeX316xZg5kzZ+LIkSPl28LCwiz2v3HjhqLgJiYmRtU4tFotEhISVB1DRERElUBlmF5mNIo/Qtvr5CJJgEYDpKcD/foF3tipUqie0+GuXHH8U1ws9nH1jw8Qz5tPjbN3PpUSEhLKf6Kjo6HRaMofFxcXo3bt2li7di3S0tIQGhqKDz/8EAUFBRg6dCh0Oh3Cw8PRqlUrrFq1yuK81tPhUlJS8NJLL2H06NGIjIxEgwYNsGzZsvLnrafDZWdnQ6PRYMuWLWjfvj3Cw8PRuXNniwANEH2e6tati8jISPzjH//AM888gzZt2qj+HIiIiMgHKsv0su3bLWfhWJMk4ORJsR+RG6pnEBQR4fhnwACxj5J/fKdOWf7jS0mxPZ8PPP3005g0aRJ+/fVX3HvvvSguLka7du3wxRdf4Oeff8aYMWPw8MMP44cffnB6nvnz56N9+/bYu3cvxo8fj3/+858um9Q+99xzmD9/Pn766SfUrFnTopz5Rx99hDlz5mDevHnYvXs3GjRogDfffNMr75mIiIg8JM9wsb6+kWe4BFIglJurbD+zGTREanA6nCNK/1H54R9feno69FbT8J544ony+48//jg2btyIjz/+GHfeeafD8/Tu3Rvjx48HIAKrzMxMZGdn4+abb3Z4zJw5c9C1a1cAwDPPPIMHHngAxcXFCA0Nxeuvv45HH30UjzzyCABg5syZ+Oabb3D58mW33ysRERF5QWWaXmYwiLEokZjo06EQKsf0STdUzyDI2UW5/EtV+o/KfL9jx9wekhrt27e3eGw0GvHyyy9jzZo1yM3NRUlJCUpKSlCrVi2n57ntttvK78vT7vLz8xUfk/i/956fn48GDRrgyJEj5UGVrEOHDti6daui90VEREQ+onR6WXa2uBby1wWvo/XY1jQaUagqNbVixlVdVXCBsIpUPYMgF8EBAPGPSqcT6Vh7/xDt/eNTcl4vsA5u5s+fj8zMTCxcuBCtWrVCrVq1kJ6ejuvXrzs9j3VBBY1Gg7KyMsXHyJXszI+xrm4nufqPGBEREfme0pkrgwcDFy6YHlfkBa+zbJU5+Vpj4cIqkZHwmK8yNVW8Ol/1XBOkhFYr/tEDpn9ssgD7x7d9+3b069cPI0aMQOvWrdG4cWMcPXq0wsdx00034ccff7TY9tNPP1X4OIiIiMiK0hku5gEQULHrhVxlq2RxcZX+Atwhtb0p7RW6aNgQeOEF9/tbGo3Ali3AY485LxCWnl4pe2fKGAQ5o9eLf2T161tu1+kC6h9f06ZNsWnTJnz//ff49ddfMXbsWJw5c6bCx/H444/j3XffxXvvvYejR4/ixRdfxIEDB1z2PiIiIiIfk2e4qP1/ckVe8CrNVmVmen4NpjbYqAhqKvcZjSLQGTDAfqGLjAz3qv/JY+jZ0zYgNidPn3z99cD47NzAIMgVvV6s9cnKAlauFLc5OQETAAHA888/j7Zt2+Lee+9FWloaEhIS0L9//wofx/DhwzF9+nQ88cQTaNu2LXJycjBq1CiEhoZW+FiIiIjIjLMZLq5UVDlqpdkq6z9OqxWIZcLVVO4zGES2JyND2bmVZvMcjcGZKVOAhARxGyjBpEIaqRIv2igqKkJ0dDQKCwsRFRVl8VxxcTFycnLQqFEjXoT70T333IOEhAR88MEHNs/xd0RERFTBDAZgwgTAfMZITIzzv/rLVq4Ehg713diMRhGMOFqPDYgL7lOn3F+O4GidixwYqp3p4431OPL7dhR8yOvQc3KADRuUFY5wdg5743M1BqX8XDTBWWxgjZkg8pqrV69iwYIF+OWXX3D48GFkZGRg8+bNGDlypL+HRkRERIC4OD11Cvj6a2DZMmDjRmDtWmXH+roctXm2ypH0dPcDIFdlwuXzK81meCujlJ2tvHKfksIRzs7hKJundD2WK4HYc8oBBkHkNRqNBl9++SVSU1PRrl07fP7551i/fj169uzp76ERERGRTKsV62rGjBEZobQ05+uFNBogOdm2HLUv1tXI67EdNZzv2NH9cystE65k2p+3Gs8aDKIinxKugiUlHK278lbfy0pUNIFBEHlNWFgYNm/ejAsXLuDKlSvYs2ePTVNXIiIiqgCuApTwcHF79arr9UKSBMyfb5mB8eW6Gr1enE9Ww+xy9epV98+r9ELf1X7eyijJgZSSqYje4iib580sX0WtIfMQgyAiIiKiqsRVgPLll6b7166JWzkDU7eu/XNOnWo6xltZEHPWQduJE6bnzHsYuhsEGY3A2bPK9nUVEHgjo6S0JxJgysSlpbne19U5HDWX7dwZiI93//z2eCu75CNVvllqJa77UOXxd0NERORlShpcXrpk2i4HQYAIhH75BZg50/a88vFr1oiAyFEWRKMRWZB+/ZSv3TEYRECgZKqXO0GQ0vPLxQPMAwV7hQ+8kVFSuwZn4UIRBCktYmFNkhz3t5Q/n3Pn1J/XGV+vIfNQlc0EBQUFARCL9Skwyb8b+XdFREREHlA6Tcs8CDK/TjIagddes39u+fgJE7y3rgZQX5a5Th3Hz9mbAqj0/PI0QPNAwVFGTWlDemdBgJosyRNPiABVqxW/X3dERQF9+thud6cstiuusk4BospmgrRaLWrXro38/HwAQHh4OJt2BghJknD16lXk5+ejdu3a0Lpb5YWIiIhMlE7T+vln0zbzTND27cD5886PV5otUHKRr2ZKGAA8+6zlhbx5luboUeDtty3ff2wsUFKi7Pw6nQiA5LXMzjJqGRni3BcuOD53fLyYYmaPmql5ALB6NTB3rgiCnntOBKoFBcqPB4CiIvEely41vUe1n78S9oLJAFVlgyAASEhIAIDyQIgCS+3atct/R0RERAHNG/1gfE1pdsE8kDEPgry5hkPJVCi1U8Lefht44QXxuSuZ4qY0UMjMBB5/3PT7NBpF5TxnU/5kGo39/c6dA5o0se2Zo2bqn0zOrKWliTEuW+Zer6Bz50xTIvV675XFNmcdTAawKh0EaTQaJCYmom7durhx44a/h0NmgoKCmAEiIiLfMQ9a5MX++fnuBTD2Llz93BTSLqVrMGqaXf61b2/6rA4dUnZ8fLzIGNm7CLe3rkYmT1fLzhaPzQseKHHunBjnhQvuBQGOXLxo+X2YM8d5ACVJ4vnZs22zT+bM12Hp9Y6zS0qsXy9uU1NNRSzUBlMyec3Whg3qj7UmB4EdOgDz5gXmHwccqNJBkEyr1fKCm4iIqLpw9dd2NQGMkkID7gRCvsgspaaK95ab6zxAkdfVzJwp7qekKLuYlo8fMgR49VXH+9mbCmUwiOyK2mlc1hYtAn76ybtTuL78Epg1S9w3Gl03bJU1awb88Yf4TOxNE5TH+Nhjou+RJ1PPFi8WP/J3Ny5O/A7KyoCdO8VzSoJKeUrknDni9+SpWrWAy5eBW2/1rHqdH1TZwghERERUDSlZ6K20lLO3+sHYG6OjEtaeNCA17/djzXytRkwM0LCh6XNQGgABwEMPiZ5BjjzwgDi/0Wh6L1OmAAMGeB4AASJb5e0pXKWlpvtypkmJ7duBTp1cr5O6cAG4917vjFv+nT31lPhdbN0KvP66+qya0kDPkeRkkZ16/HHxODLSs/P5gUaqxHWKi4qKEB0djcLCQkRFRfl7OERERNVLoK2TMRrVZzVychyPOTvbsmmnI1lZyv8K7iizJE8rio21DBbcmXZnL+uSnGy5VsNoNAVCSuh0wKOPigtuJUFCZKR4P5cvKx+3vyQlAR99JL7HP/8MvPSSv0fknEYDBAeLog/ulsz2xIwZInOm1YogaPFiUbDhxRcrdhx2qIkNqsV0OCIiIvKyQFwno2aht3kpZ0cBjNJCAVu2KAsElWSWrLMl7ky70+vF+qd//lM8njZNrNcwH9fLLysLgGrWBJ5/Xqx9mT1b2esDlmW4A93p08qC3UAhSSIAAtwLgDwNnHr0MH2X5N9zJcwEcTocERERqeNoypnSaWa+4k51M2fHKC008OKLttPa7HGnGpe70+4uXjTdr1fPNjBTmqEpLRV/9ff2FDR7JkwQU7yqc//AwYN9/xrm0//Uio0Vgf6WLUDPnsB774ntERHeGVsFYhBEREREyvlqnYw3uNOhvm5dx2tw5EIDavoMOgsE3S1BrbYBKWCZUTIPiABxof3yy+pevyJ88onoiSNX9B06tGJeN5CsXev71ygqcv/YggJRVe7CBREIBQeLfzu9enlvfBWEQRAREREpp7Qhp5oLdm9R2sgTEIFNbCwwapT9AgWAZaEBpYGQs0DQnSDNnJogyny6k3UQdOCAZ+PwhTp1gPBwy219+/pnLJVJXJy6IN1TGo34bsu/q1tuEdm7Zs0qbgxewiCIiIiILDmrUKb0QlzpgntvMRqBqVOV7SsXISgocD2lT+7Joqa5t6NA0J3MkjnzIMpVFbkHHgAaNBAXq7fcYrm/9boje+PRaCp2ncdffwG//265TaezfFyTS9ltOOrX5Cvyd/vPP8XjyrT2ywqDICIiIjJxVr4ZUJ7NmDLFt2uDrIOA7Gzl61bq1xdZIHskSfyMGycqhmVni8aSn3xi2qdDB2WvYx4wypX05MpwagIhjUZUd5MbkLr6HQEieDt+HLhyRawJSkw07X/+vGm/4GDxeVh7+21Tk1l/WLIEuOMO4JlnxOObbwbWrBGfRUVmPiorX39GV6+K2z/+EKWyCwt9+3o+wCCIiIiIBCUFD5RmM86f912RBHtBgNIF5dOnAytWuO5Zc+4cMGKEKcD44gvTc0qzQomJIvh54QURUHTrZmpQWcPqEsxRUGbe30erdfw7OnVK9OKZMsUyM/TUU8CgQY6nCl6/Dhw5Yru9fn1gxw5x6+0LantBl7W5c0WBhE6dxOOoKFNWLilJ+WtFRYlqaNVBfDzw4YdAZqbvs0MNGpjuDxwoKuxVMgyCiIiISHnBA0BZo0VfFUlwFAQoLfl7662ifLQaubmmHijduokxOAsE5cxNfr64AM/IsB2f+WcyeDBw9qz4i3pYmOV+Op2pPLaz35Fs4UIxxvr1Ra+gf/3L+XsLCxNT0azdf7/IxAwb5vx4d/Tu7XofeTphixbiPYwfL7br9aaKZK5kZorP/bXX3B+ruebNRVbNEX9nqM6dE793Z2NUokYN19/t7t0tt7NENhEREVVKagoeyH+Rj452fk5vF0lQEgS4sny5+gIF5q8XH29ZMMGafPHYti0wZIjrSly1awMrV4pz6vXAtm3i9tZbRQZn+XIxHQ8A5sxRPuXv7Fkxpc2Va9eAV1+1/1xurnjuiSc8L1udliaaai5dCoSEKDsmLw/Yt098NjffLAKi5s1FzyMl5NLgd93l7qjF7/P//k/cLysDPv5Y3I+PB+bPB559VgTlcXEVuzbHEblflSfktXXWgZB5VtL63z6DICIiIqqUlBY8kPfT64F//MO753ZFzbofRy5d8qxAwfXr4lYOBK2nWul04iJywwZl57t40TJIPHkS2LwZ+OUXccHds6eYjvfUUyKj5AvLl9vfLq+Pevddz4Og7Gxg4kSx1ur995UdU7cu8Nxz4vP85BPg8GHg6FFg0yZlxwcFAfv3i3UrgAgOHL1XcxkZpsaw9euLaYaAmEIpFwJo0ECMq107kcEzX2flKY1GfI9eew0IDVV3rNyw193v95NPiszbunW20xbNs5IhISLQlrFPEBEREVVKSv96bL6f0r/+Kj23s4pnBoPydT/WgYn5Av+iIvdKX8s+/RSYNEnc1+tFdkY2fbqocKZ0upZMrqQnT/Wzzh6dOuV6WpsnXC1qv3DBtBDeG5T0qalRQ5QvP3pUPFaa/QFMU7YWLwbatBG9hwCx7mrQIKBJE/vHxcSI78WmTSIQqlsX6NNHZOsAMW1QDlhr1/ZOZtLe2AExjlatgOJi5cfJxTPc+X5HRYkeRa+8Ih7r9cCxY0BWlshUZmUBOTliu3xeOSAMD7dtxlsJsNYgERERKeuxY16hDBAZCmfkv2ibH+OIwSAuKM0zPTqd6WJOrqqmxNq14qJMnhp08SLwt7+J5+QLcDmTM2mS+nLeGzea7vftC8yYIbIE8fHA99+rzwo8+qio0jZ1amBMqapIcrlya2Vl7mX9zKdsffCBuB8UJIKomBjgq69syzrHxIjv3nPPie/N+vVi++uvi7Lc5tUA5SazV664nkLqDp1OjF2vF38MUEMungGo+35HRYl//8HBltu1WjGN0RH5c6yEU+EABkFERESktMfOggWWf/E1/yu19cWsdVUzZ+QMiPXFcG6umIoUG6ssOJCDrkaNxF/qu3YV2z780LSP+QWwXi8u/saNc31uc5cvm+7Xry+KB7z+ugiE3Jn6V1KiPMtV1cTFWQbgERGWn69a5kHE4sVi25Ilzo/56y+R+Tl6VGQ85KBh0yYxFdDed2/nTuVTHpWIiRHBe1qa6d+L+XQzZ6KixDQ/OUsj0+vF2p2ePZ0fX1QkgndnAY89jz2mbpwBhtPhiIiIqjulf9GOi7N8fO2auL3rLtu/BsfFib4u1hdm1pRUpXNVztqcfAEcGysyNlOmAA8/bHr+0iWRZZBfe+ZM5eeWWVd6k8tbnz/v+aL06iYz0zTl6o03PAuAZswwTdkyGMR5lZC/Zx9+aJk1+egj58H3Rx+5P1Zrb78N9OhhCoAMBuVrwCIjTcUzrCmthOhO8C7/O7jrLvsNewMcgyAiIqLqTm1RBJm8TmTHDjE9yNy5cyK75KpPkLemFEVEiOk//fqJC2F5vN99Z7uvfKG9fbv6ctmAyNzIVcKyskwZgfPnTYvSqxPzdSdq11iFhABdugBDh4rS3p6Qgwg5sPaUHOQ7cu6cmALpSWlsrVZ8l8z/WOBobZgjubmOKzC6s9ZPCYPBFDDu2GG/YW+AYxBERERU3bl7oWRegMDeX4HNm6w64q3KcZcviylKDRuaLh4ffRQ4cMByv2efNV20evLagweL97V8ObB3r9h2/ry4GB040P3z+pPaSmQynU6so1m/XlkjVHOffSbWotSv736FMfOiAIBv1uo4Mny4Z8evWmX5fXG32IKj77KrSnHWn50ScpBWUmK5Xcm/9wCikaTKuwKvqKgI0dHRKCwsRFRUlL+HQ0RE5DtGo7i4kxf7y1WgvHXulBRxEWPvskBea5OTY/uaM2ea+qjYIx/7++9i3YH1+LOzPc8AKJWRAcyaZXrs6WvHxIjeNXK2qWZNoLTU9LyjRf+Bqm9f0QRzyhR1x61dK6quAZbf06NHlU/pqlFDrONS2vTWnEZjKt0MiMDCF01e7cnKEmMeO1ZdQYzkZNPUTXPufiezshyv6ZGDFsD+uj3zz84V+b8VjoJMZ/+tqACqYgOpEissLJQASIWFhf4eChERke+sXy9JOp3ctUX86HRiuzdfQ6OxfA35R6Nx/Frjxtk/xvonPt7++EtLxX1Hr+2tn/BwSTp50nLspaWSFBnp29cFJKlTJ0navLliXsuTn549JWnlSnXHaDSSlJwsPkt7Bgzw/bhnz7Z8zaysivm8zN93SYntd9zRz+bNjj8vb3/+5v++rf8bkpys/r8hSj/brCx15/USNbEBp8MREREFMvmvuNZ/efX21BO5pG58vOX2OnWc/6VYbh7qinUJ7lOnROU3g8FUBtuXrl4Fdu8W2Ql5upxWKyrI+drhw+Kv9P/+t3fPa90PyVObN5v68iglSaLBq6M1KR07mu63amVbXMMbmjWzfKyk3Ls3mFc+DA4Gli4VmRBHU8/uvBNIT7csgGBNzdocNRUYXfX9Ucrd9YOBqAKCMp9hJoiIiKo0OUvi6V+B1b5mVpb4i3RWlvNzT5zo+V/TtVpJ+vhj8RfpiAjf/uW+eXNxa/7X72++kaRBg3yfpZE/ywkTvHfOzZtNv6vGjb1zTp3OvczcypW234/16yWpTh3ffq7yZ2v+/XX2b8ZbP5mZ9v9N2Mu41KkjSWPHSlJBgbJ/f0o/f3cyOZ6qQpkg9gkiIiIKVK4WeEuS6a/want8OOKqQaK548c9fz2jUawnWb8eePBB8VdqX5EXcv/4o7ifmCjWwNxzjxhHdrb4AcRnO3euqZy2pzZsEKW6vbFgX153kZYGnDghMlt//imeGzMGWLbM/XOfOgXMni3WTqlZ02SdwXDU+8mb7DXjVVoUITMTqFdPZL5mzVI/TkfFL/R6UaHQ3fV7Wq3IjA4c6PjzT08Xr+HNdYFKyYUWXK0fVFNowU8YBBEREQUqf0w9+fZbcdu6tWiGeuECcNNNYuG6NesSwp4UAkhPB15+2bdB0MWL4nbePNO2uDhgxAhxUZmWJqYqydq0MS3499TCher2d/RZWk+BWrUKeO45oFYtICjIswBI1qyZmAI5ebLrgMLeRa+7Fc7UcDQVTOm/hXr1RFluAGjZUjT+VFOU4eBBEeDYC0Ls/SGhsFBM04uJcT2NUZ6aav35OyqmUJGcBWlqpucFAK4JIiIiClS+6vHhzCOPiHUy+/cDCQnALbc4vjiU+wQZDPbLI9sLnBw5eRJISjKtSapXz7P+K/YUFtpuO39eXLTZ63MycKB4X572/VHzOcjki0vrstERESJ7dfPN4rHcqPXKFVOQ54j1ei9HEhMt15Ckp4vt1r8PRxe93ixRrdGI92j9O9Dp7K9Vc+ffjF4vKtyp0bu38r44P/8sPsNmzYAhQ5Sd31treHxBDtKs/707+p0EKAZBREREgUppj4/OncU0rlWr1HVul6eAmR8nBwqxsYBcYtZRECRngsLCTBdt//mP6Xm1U8ny8kyvOWmSumO9wV6xCfl9bd7sfiECd6fUaTSibPSTT4rHDRuKjM+WLcBff4ltdeq4Pk9MjBj/qVPOv0+ACGbkUs9yRiMz036Q6+ii11uZSXmcy5YpDwjc7YuTlub6s7GmtDjJlCnAihXifnS08vPLn//QoeI2kLIrgRykKcQgiIiIyB32Aghvk6eeAI7/Cv/QQ0CTJiKTMWyYKaPx8cfOx2cwiP2sj5MvriMiRHADAJs2mY43f9/yxfLZs0DTpuIcxcXuZT7k9yRnl26/Xfx1PjLSvXO5Q86+pKdbfl5arZgm9/bbFTcWeTynTple9/hx4MwZcX/tWjHG06ddn+fCBfEegoNdV+IzGk2NYM2pueh1JzMZG2vKasnMgyylAYGSfzP2pms5O84RR98Xa+HhpvtVqa9lIAdpSlRAoQafYXU4IiLyi4ro22P9eklJtpWhnnxSeRUv8/E56glkvs369WJiJGnIEOeVt2rXdq/fj1zlrn5907apUyumypea6lbr10tSaKj/xmT9ExsrSQ8/rGxf8+pta9eKqnyufh/uVh10VeFMoxHPL1kiSffeK0kjR4pKdyUlyisTuuJuXxx7x7n7fZE99JBpv/R0998TucTqcERERN5gNNpWedqwwX7VK3lqjCdz4uXXy80Vi6jj48UUpH79gHbtRKYGAIYPFz1nmjSxHYcj8vjWrAGmTrV/nPk26wzDhQviWGeKipSPR2b+1/lHHjFtX7BA3Xm8zXpKV0VUO1OroAD44ANl+5pnZ+LjnWcuJMmzqoNKFs8PHQo89RRw+bJ4/N57IvOzaJGpYIEn3K3SZn3coUPAiy+6fj1nUwCraiaokmMQREREZI/BYFudqX59Md3LUQCh0ZjK16qdGmLv9WQ6HfDEE6bH8fHA99+rW3wuj2/CBN81k3Rn7YtOJwKg/v1NZYfDw03T4vzFPGioiGpnvmKveltFVB10VOFMpxNTOF991Td/SDCnpty7o+Oys5UFQc6mANaqZbqvZk0Q+RTXBBEREVmT/+pvHWTk5oq/vjti/hd0b7ye7NQpU4UuQFQCc+cCVZJ8FwCpER8vCh9kZopePDExllkkdwOg+HjxOW3erH6Ru8zewnml1c5GjFD3WsnJouiBRuP9SniA4zUwFVV10N46ot9/F+vJnGUiXa2xqUjuFlowx0xQQGImiIiIyJw3/uqvJkBx5/VGjQKuX1c9rICQmSlKYU+caBmQyRfc7vQamjFDFC4wn+4kT8dSS5Lc7z1z333Ap5+apnjZEx8vPoP69U3j7djRNmMSH+95wCpn2ayzKhXZ8NI6G5OdXfENgD3hjb445kFQq1Y+GSapx0wQERGROW/0OFHzF3S1r3fbbaIktqu/UAcirVZkA4YMsb3AlwMNNe9H/iv8rFm21akc9TJxJTZWTGc0p/T3Wb++6B/jaKwaDbB0qVjTZT5eexkTuZy1u+LjRdbF3rQydyuoeYM/GgB7ytO+OPfcA/zrXyJDeeedvhsnqcIgiIiIyJwnF19KpsZ4+no9e4pbd0r6+pvRCHz2mfN9lK4rUnKxrteLstKzZyseIgoKbKczKgk45f46990n9rUu7e3qgtm63LCSctbOnDsn1o054q+Gl/5oAOwNnvTF6dRJrOnr0cPnwyTlOB2OiIjInLsXX+YX5YCY9qOkKpXa10tMBL79FujSRaylmTwZeP99xw1NqypHU72sabXAzJlAy5bAY48p+5ysA1PzKVGOyP111q0T07nsVRZUm1nR60WT0jFjnK9FU/o+7J3fnQpqnqjIqXje5m6hBaNR9HUqKgKaNQO6dq18PXWqII0kVcZSJ0JRURGio6NRWFiIKC40IyIibzAaRSlqZxdpMTHivvmFaXKyKQCyVxFr0SL7F+zXr4vnXa3/0GiAuDixX8OGYpzmrxEUJMZbWqrkXTp3zz3A7t3+DawSEoDCQuDaNdO2+HgxlaxfP/cu1rdsMWXSnMnKsn+x+/HHIlPjaNG+RiMyK6++Chw+DLRuDfTt6/kFr9EIzJkjvkNqfieO3oe/yYVAAPtrbHyZiapoBgPw+OOWJeed/feAPKImNuB0OCIiInOu1kvIF23mAVBUFDB/vrjvqKrcwIHigsicwSB6/ShdAN+1q7g9ftz2NW7c8E4ABIhgKy9PrN3xl/PngRYtxP2pU8UFfV6eKCrgbnf6tDTPKn0p6a9z6pQoAT1rFvC3v4mA2vr3rpaczcrPF5/Dhx+KsXhSscyf/DUVr6LJwZ51zy1H/z2gCsVMEBERVX3uTE0yGGynIcXG2p+WJAdHjp6XxcSIaTFpaY6brtqTnAw0bSougH1Fq7W8wJf/Wl1WBjz6qJjKU9FCQ0VfpnffBUaO9M4UIk+yEKtWAcOGqXs9X2U3qkI2xRtTBgOVnFF2VPREnvaXk1N13nMAYCaIiIhIZjCIi5Fu3cQFbLduyv46r9eLrINs4UIgLMz+vvayQ/ZcuCCmY9WrJy7qlQRAb70lLpTkKXi+Yp3hkP9aLUn+621SXCxuH33UOxkVwLMshDvrxXzV+6YqZFOsi0FUpWDAVdVHd3uKkdewMAIREVVd8l/L3e1Mf+WK6X5Jieels2VqFrknJoqLw8JC77y2UpIk/lo9YYK6fjXu9PlRQunvTAl3CwK4WtTviK963/ijsAEpUxlLgVczzAQREVHV5KwJqdK/zstNLxs39n0mxp633gL69BH3KzoIAsTnpLZhp04nKpqtX2+bOUlOBp58Un3vHnksgPcyKu5kITwtS+6LC96qnE2pzCprKfBqhEEQERFVTUqno2RnO97n0iVxe999Yk1ORTt9Gti2TaxFOXOm4l/fHfPniwyFXg98/rnYFhVl6qvyyiuisENGhvpzB8IUInebsAK84K1OXPWWCvTiFdUAgyAiIgp8RqMIVlatErdKMgFK/+o+eLDjtSZyJigiQtlFTUSEstdUavZs01qmkyfFtltuMb1eRXFWicycRgNMm2b6/ci/gyZNLLMU7vZbkfl7CpF148zNm3nBS5ZcVZkEnDf6JZ9jEERERIHN3cIGSv/qfuGC43K1cibo3XeBH380XdTYI0mmoMmXDh0SgUZFTM+TL96XLFG2v3mm5rXXRI8cwH7WxJNAJhAyKubT0Hr04AUv2aoKxSuqMAZBRETkW+5kcWRyYQOlfXfMucrcWLO31qRxY3FbUAB89ZXpokans9wvKEiUx64omZnKF+bHxQEDBgDPPivuK/08zC/e5YIESgOvvDwgPNz02F4Q5G4gE6gZFV7wkj3WWUN5Wii/D37HPkFEROQ7BoMoTmAexCjtlq60z8bvvwPff2+/OpbBIAIApbKybKdpPf20WMcyZQqwYIFpbNu3A998A8ydK8Z57Jjy16komZmiW73552Gvt4w9yckiADL/PW3ZIkp8u5KVJQoqDB4sgqF33hH3zTMh8u9XTaU1jSbwA4qq3PuGKMCxTxAREfmfJ1kcQHlhA53O8VS5Pn3U9bixN0VLXucjl8u+cUNUauvaVZQnBipmGpw76tWzvAB3lK2IjxfFHwCxfsfRX6vT0pStfTl/XpTWBoCrV8XvxnoKo9pKa7GxgR8AAazWRlRJMAgiIiLv80Z5aqVrRqxLOMtB1lNPiYv9oiJl5wGAunVtp+7VqiWekwOd/fvFBXmTJkDt2uI14uOVv0ZFsjflzN70nLw8U8asRQvHF+9KFns/9JDI+jj6vZgHQkoqrcXEiAIRZ88GfgBERJUGm6USEZH3qemW7qhKmLtrRuQg61//UndcbCwwapTluIOCROYHEEFQdjbwxRficZ06wE03if3dmdrlS/JUQUdrZ+xVZ8vPF7d16zo/txy42JvmOH8+MHWq4+BXoxHBb79+piDLuuGn/Pr5+ZxORkQ+wyCIiIi8zxvd0uXCBhUVWBQU2G6TAyAA+Ppr4LPPTI8PHgQ+/hgYNEg8fuwx93rfeJs71ch27QLmzBH3XQVBgG3gIgcr7ga/npbMJiJSye/T4XJzczFixAjExsYiPDwcbdq0we7du/09LCIi8oQ3uqWrXTPirho1lFU9KymxfHzjhpj21b+/yAI5CoBiYoAhQ8R78MX7CAqyfOxONbJVq8TaHUBZEATYX/vijeCXiKgC+DUI+uuvv9ClSxcEBQXhq6++wqFDhzB//nzUrl3bn8MiIiJPeatburOF/N4ycKDoFeSuDRscZz9mzxbTulavdr32xZrS99ili+fldyMjTfeVBkH2eCP4JSKqAH4NgubNm4fk5GQsX74cHTp0QEpKCnr06IEmTZr4c1hEROQpb3ZLlxfymzt1Sl0PIEf++U9g7VrPzuGIRiNKQ8vk97F5s/PMkxwgnjolgpr0dPsBUUiIuK1d2/NqZHIFPAA4fVpdLydz3gp+iYh8zK9B0GeffYb27dtj0KBBqFu3Lm6//Xa8/fbbDvcvKSlBUVGRxQ8REQUobzaPtL6wDw72zlS5Tz5x/1hXzNe/yLRaoEcP4O237U+PMw8Qg4NFUJOZKaaPyQFRdLTYR56e9803rsuNO2MwiF5Hsqeesi1nrZQ3g18iIh/yaxD0559/4s0330SzZs3w9ddfY9y4cZg0aRLef/99u/vPnTsX0dHR5T/JyckVPGIiIlLFOosTFOR+t/TOnU33jUbHQVZyMvDkk46DDI3GlFk5c0b9ONSyt/5FbYCo1Yope4sWiR5F5q5eVdZ3yR65l9Nff1luV9rLyR5vBr9ERD6ikST/1fIMDg5G+/bt8f3335dvmzRpEnbt2oX//ve/NvuXlJSgxGxhalFREZKTkxV1hSUiIj8aPRpYvlxM3bK+4FaqtNRUBCA/3xTIGI0i25KbK3rTxMeLC/Dz54EpUyzX6yQni0zEkiXA7t3AxYsevCmFsrIcVz6Tx25eYc1elkQuwe1o7ZFcEjsnR3mWxRfntD6/kvdGROQlRUVFiI6OVhQb+LVEdmJiIm655RaLbS1atMD69evt7h8SEoIQeQ40ERFVHk8+KYIg88yMq4tke8/HxopS1uZB0KFDwPvvi/495g06dTpgwQKxn/Vr9OsHJCQoG3tIiG1lOCVc9eoBlJeG9kbfpYo4pzmWvSaiAObXIKhLly44cuSIxbbffvsNDRs29NOIiIjIJ+rUEbcXLwJlZcCnn9pvtrlokZguZTDYf/6WW0RQY14WetEiEWBZy80VJaxvvhkYMEAUDpDNmSMyRUq4EwABIojw1voXX5SeZjlrIqrG/LomaMqUKdi5cydeeukl/P7771i5ciWWLVuGCRMm+HNYRETkTdevA/v3i/uSBHz4oVhvYp2FkNehPPWU/edPnRJZidatxVS27GxxbkfV3eTZ3ocPi2yRzGComKamkyZ5b/2L0pLSR496/5wsZ01EVZBf1wQBwBdffIHp06fj6NGjaNSoEaZOnYrHHntM0bFq5v0REZGfnD5tuUg+IcF5QQKtVnmJ5rg4ZRmd/v1FJThX62CUGD4c+Ogj1/vFxwNLl3onEDIagYYNRaDojE4nClEoyT7Jn0VurilgNOfpmiAiogqmJjbwayYIAPr06YODBw+iuLgYv/76q+IAiIiIXDAaRbZk1Spx627vF09dvWq637u364psasapdEpbYaFpjZEnARAgPs/YWNeluc+fd7/CmjWtFhgzxvV+crZM6TlZzpqIqim/B0FEROQDBoP4K3+3bsCwYeLW3d4vnpKDoHr1gBEjKv71AVGhLSUF2LDB83OVlYniDK4mUsjPp6d7JwBt1kzZfmrW8LCcNRFVU34tjEBERD4g936xvkjPzRUFAmbPFhfUFVW2+No1cRsW5t/1Jbm5IrPhLXI2yFk2ytMKa+Z8tYZHrxfV8ljOmoiqEQZBRERVidEoqqrZy1LI28yLAphXZPMVORMUFiaKGtSvL9YJOcqkaLUi2+LtJavy+dSsOXKmoAB49lngpZdc7+uNCmupqeL35WoNj7OS3I6wnDURVTOcDkdEVJWoXfMiV2Tz5TQ5OQj69VcgJsZ0sW1vHYpGA/Tp4/0AyJyrAKiGiv81Kt3XGxkwruEhIvIaBkFERFWJ2oyDt9et2CvGYF4YARBFCmbNsl2HEhcHPPCAd9btuOvJJ4E1a5Tvn5Ymsi+OiiRoNEBysnvZGXu4hoeIyCv8XiLbEyyRTURkJTtbFEFwR1aW+1OijEbRgHTRIuDCBdN2nU4EFj/9JAKj0lLTcwkJ4vnSUuDECcvj/CU5WZSENhhEc1VHgaF5+egNG0Q2DbDMYMmBkS+CE7nSHdfwEBGVUxMbcE0QEVFV4mrdiDPurltZtw549FGgqMj2udxcsUbJnjNnXJfLrmhyEYNBg0QQM2iQ7T7WU8/k7MzkyZZTEXU6sY8vsjNcw0NE5BFOhyMiqkqcrRtxxZ11K089JQIFewEQ4Ju1PQ0bAu3bi6IE4eGWz9WtC9x0k2fnl4PBgQOB9etFMGPO3tQzvV40Kc3KAlauFLc5OZyeRkQUoDgdjoioKjIYbDMTjphP7VIzperjj4HBg90fo7vMp+2lpQHbtgHjx4tgbMkSMS5vnR/g1DMiokpCTWzAIIiIqKoyGoGa/5v17KjstLN1K84u/o1GsabHWY8cXwgPF1kneRwpKcDx48COHUDHjqK4wsWLjo93Vn7b3WCQiIgCgprYgNPhiIiqKvML+eBgEegEB1vu46iqmMEgAoxu3YBhw8RtSoqplHZ2dsUHQABw113ifUmSqDp38qTYnpcnxuQsAAJE8CZJLDFNRFTNMQgiIqrKGjQQtzExItBp1cr0nKN1KwaDWA9jPZVO7in0xBPA3/7m23E7csstYgpezZoiO1VWJrYPGqR8al56OktMExFVc6wOR0RUlb32GtC/vykYMi9Rba+6mNEo1hLZmy4mb5s/39ujVC44WARjZWW2xRiUltju1w949VWu8yEiqsYYBBERVWWhoeK2uFjcXr/ufP/sbGXFFJSKjQWaNQN27gRq17acriZXctu+Xfn58vKA/fvdG4u85kcOeFhimoio2uJ0OCKiQGc0iuBk1Spx66iBpzVJAm7cEPflIOjppy2fN7dunXenuXXpApw9C9SpIx6/+qrYBogpdadPAxkZ6s556hRw5Yr7Y+KaHyIiAoMgIqLA5qpAgTPXrgF9+4r7X38tbgcOBB56CBg50jKYkvv9XLrk+ZiDg4GZM4ENG0TAce2a2B4RAdx8s7gfHS2eHzlS3bndrQSq1QJr13LNDxERAeB0OCKiwCUXKLDO2MgFClwt5L961XQ/KUnc1qolMkrmPv4Y+Ne/vDNmQAQqM2eaMi6jRomqbi1bAgcPim07dgDPP6/uvHXrAo8/LoIntYxGUT6biIgIDIKIiAKTqwIFGo2octavn+PpXXIQFBJi2uebb8TjDh2AsDDxOuPHe3fs58+LdT7ymhvzbE9iorj99lv15x07VpwzNhYoKFB/fF6e+mOIiKhK4nQ4IqJANGeO8wIFkiR65DgrKiCvnSkpERkUQFSKS0sD/vhDVFjbvt03/X4+/BBYs8Z2e9264laeIqeE3Nvo9ttFMPfkk+6NSQ7AiIio2mMmiIgo0BgMygsGmGc3jEbLss/h4abn3nhDFAWQg49WrYCjR8XUOl94911RxKFePVEYITRUVHWbOFH5OSZOBAYMEAHh5s1i6t/XX4uiCgcOACtXKjuPeVU4IiIiMAgiIgosRiMwaZLy/eXshsEgps+ZZ4/i4033JQn46y/LY7/4QgQY3lajhsgy/fGHKOTgrgEDRNZq0SLTtm+/BR591PJ9xsQA99wjCh8AllMINRpxy6pwRERkhtPhiIgCyfbtyrMz8fEiuyEXULCePnfunPPHU6b4ZipcWZlnx2s0QHKyKXNTq5bpOXvTBP/6SwRATzwB1K9v+ZxO57qABBERVTvMBBERBRI1i/eHDxe3jgooWPNFwGNOq1Xew8gRe5kb8yDIHrlQxOrVIvv0/femKYFyY1QiIiIzzAQREQUSNYv3+/UTmSNnBRTM+TIImjDB8wAIsJ+5efBB18fJhSK+/15MoRs6VNwyACIiIjsYBBERBZLUVNspXfbIC/3VZI6sp8N5k5zB8URmJpCTYzt17YEHRKNVJVgGm4iIFGAQREQUSLRa4LXXXO+3aJHYV03mqH59Zed2R5Mmnh2v04ky3o4yN6Wlys7DMthERKQAgyAiokCj1wPr15v641hbscKULUlNFQGEs0xMaCjw55+igtrjjwNPPy0apTqjdBqZXMRg/HjX43Dm2jVgwwb7zxUWmootODq/dTEFIiIiJxgEEREFIr0euHpV9MeZMUP8NGoE3HEH0KOHaT+t1lRC2lGA0L27OFYOql5+WTQz1WgcH7NqFZCVBcyf73iM5kUMgoMtS1mrdeGCqHBnMNg+t349cP060LChqQiCo3FwDRARESmgkSQlJYUslZaWIjs7G3/88QeGDRuGyMhInD59GlFRUYhQOm/bC4qKihAdHY3CwkJERUVV2OsSEfmNdUNUufqZwSCyPKdPm/aNiAAuXwamTwdeegk4dkwUD0hOBlJSRAGC8eMt1wolJ4tgQs40nTsH1K1rfyzW+wL2+xUpJTc1zckxBTMGAzBmDFBQYNrPugqdvXEQEVG1oyY2UB0EHT9+HPfddx9OnDiBkpIS/Pbbb2jcuDHS09NRXFyMpUuXejR4NRgEEVG1Yi/AiIsDRowQleKCgoC77jI9N3w48NFHIrAYMgQ4cQL4+GMRVPTqJc5l3pMoLg5YsgQYNMi0rbRUnFeWleW6/LTRCGzZAsybB3z3HVBSou59ZmWJym5y/yNH/5tKTxfvm2WwiYgIPg6C+vfvj8jISLz77ruIjY3F/v370bhxY2zbtg3/+Mc/cPToUY8GrwaDICKq0rp1EwHIBx+IYMJZQACIIEYug/3GG+K4nTtNz9erB5w96/h4eVrZ2rXitQAR0NQ0aylXWqos4Pj4Y2DwYMttkZHApUuuj125UhybkuI4o2Qva0RERNWamthA9ZqgHTt2YMaMGQi2WrDbsGFD5Crtck5ERCLAyM4W62+ysy2neJWViW2bNonAZ8wY1w1R5QCoZk3Rt8c8AAKcB0CAOL8kiWl1RqPIxKSkWO6TkmJ/3Y45g0FknqwpCYAAkWVy1f9I7gu0fbuycxIREZlRHQSVlZXBaKch3qlTpxAZGemVQRERVXlygNGtGzBsmLg1DzAuXzbtu2SJ5ZoYV5SWk3bkzBlgzhyRDbIORHJzHRcwAETwNHmy64DNHvMKb0r7/bAvEBERuUF1EHTPPfdg4cKF5Y81Gg0uX76MjIwM9O7d25tjIyKqmuS1Ls4CjKIisU2rFVPbKtqiRfYDGXlberpl5krmKoPjiHWFN6X9ftgXiIiI3KA6CMrMzMS2bdtwyy23oLi4GMOGDUNKSgpyc3Mxb948X4yRiKjqcJYpMQ8wLl4U98PCRPnoiubsNZ1NRVOamYmJsXys04lqdUr7H7EvEBEReaCm610sJSUlYd++fVi1ahX27NmDsrIyPProoxg+fDjCXDXfIyKq7tSudQkJsZwaVxFiYpQFXvYCHqWZmbVrRcbHUaU5uf/RwIEi4DEPGtkXiIiIPKQ6CAKAsLAwjB49GqNHj/b2eIiIqjalmRI5UIqMVLceyBsmTwYyMlzvZy/gkTM4ubn2s11yVbe0NNcBjF4vskPWZcF1OvYFIiIij6gOgt5//32nz//97393ezBERFWe0kxJVJT4SUoShQ4cBRXelpgIPPcc8PbbrgMZe1PRvJ3B0etFLyB7DWKJiIjcpLpPUJ06dSwe37hxA1evXkVwcDDCw8NxoQLnrrNPEBFVOkajqALnLKiJjxeZj+Bgsc8nn7juEaSWHKDMni2m3D3zjNj+7LOiMpxcvAGwH8iYr9+xx15j1+RkZnCIiMhnfNon6K+//rL4uXz5Mo4cOYK77roLq1atcnvQRETVgpwpARwv+j93DmjSRAQSGo1pWlhcnPfGodMB69cDM2eKEt3x8cCtt4oACDC9Zv36tse5CoDk448dA7KyRPPTrCzR2JQBEBERBQDVmSBHfvrpJ4wYMQKHDx/2xukUYSaIiAKW0eh4CpfRKIKNRYscFyCwl3G5fl0EIefOeTa2zEzRTDUxUUy5++kn22ptSt4HERFRAFETG7hVGMEerVaL06dPe+t0RESVl72pYDqdKQNk/Zw98t+nHntMrInRasX0uKVLgQED3B9baKiYjhccLB4XFIhtX34pxtS4sWjcKgc6Wq0oYkBERFSFqA6CPvvsM4vHkiQhLy8PixcvRpcuXbw2MCKiSkleS2OdZM/NdS94uXBBZGLkQESvF+Wlhw6136zUlS5dgJpm/+kPCgJuusl+wMapa0REVEWpDoL69+9v8Vij0SA+Ph7du3fH/PnzvTUuIqLA5WiKmJJGqO6wLqs9aJCYLjdokPpzdeokMj+yGzdss1K5uSKQU7L2h4iIqBJSHQSVlZX5YhxERJWDvaluMTFiW5curqe5uaNuXdttAwcC6emi2porAwaIIggAcOmSZSbIHkkSQVZ6umkqHhERURXitcII/sDCCERUoRxNdZNFRACXL3v/dR1NT8vOFut3XImOBgoLTY/r1gXy85W9dlYW1wQREVGl4PXCCFOnTlX84gsWLFC8LxFRpeFsqpvMFwEQILJL9qanpaaKAMlVI1XzAAhQV13OeioeERFRFaAoCNq7d6+ik2kc9bwgIqrstm/3zVQ3pSTJdnqa3HNo4EBT81Ol51IqMVH1UImIiAKdoiAoKyvL1+MgIgpsgZAROXnSslIcYGpqar1OKT7es35CGo3IMqWmun8OIiKiAOW1PkFERFWaLzMiarI49oIxvV5kiMwr1uXmAiNGuPf6clZ/4UIWRSAioirJrSBo165d+Pjjj3HixAlcv37d4jmDweCVgRERBRR5/Y2nU+KsA45u3YDr14HvvlN2vKNgzLqpaXa2svM98giwaZNtn6CFC1kem4iIqqwaag9YvXo1unTpgkOHDuGTTz7BjRs3cOjQIWzduhXR0dG+GCMRkf/J6288JQdAcq+erCzlAVB8vPLpaXLQ5mqt5vLlYkyzZwMrV4rx5OQwACIioipNdRD00ksvITMzE1988QWCg4OxaNEi/Prrrxg8eDAaNGjgizESEQUGvV7024mNtf+8muIwxcXqX3/JEuXT08yDNlfjOn0amDULCAkR2SROgSMioipOdRD0xx9/4IEHHgAAhISE4MqVK9BoNJgyZQqWLVvm9QESEQUEo1FMMSspAV56SWyrYfWfUJ0OyMjwzes/+aSoAqeGXDShfn3n+8nZqfR08T6JiIiqONVrgmJiYnDp0iUAQP369fHzzz+jVatWuHjxIq5ever1ARIR+Z3BYFt9DQDi4sQUMnn9jVYLvPOOd187Ohp4+21g0CD3jpeLJrz+OjBliuP9JMl+9TkiIqIqSHUQlJqaik2bNqFVq1YYPHgwJk+ejK1bt2LTpk3o0aOHL8ZIROQ/BoPIwNir3pafDwwZAhQU+O7133jD/QBIptUC9eop2zcQSoETERH5mOogaPHixSj+31z26dOnIygoCDt27IBer8fzzz/v9QESEfmN0SgyQM7KV/syAAJcT2VTSmmJbzZHJSKiakAjSWpahweWoqIiREdHo7CwEFFRUf4eDhFVdkajZa8doxHo2dM/Y5GblebkeKdQgdEIpKSI/kH2/rPv7dcjIiKqYGpiA9WFEbp164Z3330XhYWFbg+QiCjgGAwiSOjWDRg2TNwOHuyfsfiiWamzanFsjkpERNWM6iCoVatWmDFjBhISEjBgwAB8+umnNg1TiYgqFXndj3XhgwsX/DMenU5UdfN2rx5H1eJ89XpEREQByq3pcGVlZdi8eTNWrlyJTz75BFqtFgMHDsTw4cPRtWtXX4zTLk6HIyKPydPErAMgX9Bo7E9Fy8gQzU3z88U0vNRU32ZkrKf9+fr1iIiIKoCa2MDjNUHFxcX4/PPPMWfOHBw8eBDGCuwxwSCIiDyWnS2mvvlaq1bAuXPAmTOmbcnJYgoaMzBEREQeUxMbqK4OZ+7MmTNYvXo1PvzwQxw4cAB33HGHJ6cjIqp4FVUS+uabgb17gW+/BU6cABo2ZAaGiIjIT1QHQUVFRVi/fj1WrlyJ7OxsNG7cGMOGDcPq1avRtGlTX4yRiMh3PC0JXacO8Ndfrve7eFEEPBWRdSIiIiKnVAdB9erVQ506dTB48GC89NJLzP4QUeWWmioKAzgqHe3Kc88BTzzher+KWHNEREREiqgOgjZs2ICePXuiRg3VheWIiAKPXDp64EDHhQsciYkBEhKU7VtYKKrQvfce0KsXMGGCe+MlIiIij6mOZHr16sUAiIiqFrl0dHy85fbYWHFr3VdHNmaMbblpR65fB37+GfjsM+DAAffHSkRERB5jNENEBIhAaOlS0+M77gDOngXWrwciIuwfc889YjpdvXqOz6vRADVrAi1bmtYO1anjvXETERGRagyCiIhk3buLktWAqBqn1YrgaMgQsa13b8v9a9US+4wcaf98cgZpzRogK8vUfDUmxutDJyIiIuUYBBERyaKjTT17zpwBysrEfTl4uf9+y5LWcobowQftn0+nE9Ps5HMyE0RERBQQPOoTJLt48SJq167tjVMREfmXPLWttFQEP3FxQEGB2BYfLwKY8+fFYzkIsp4Ot2QJ0KKFbR8gZoKIiIgCgupM0Lx587BmzZryx4MHD0ZsbCzq16+P/fv3e3VwREQVatUq4K23TI/lRqpy0BMbC8yYIe43agTI3ajlAgqyxx4D0tJEAGQ0Am3aiGDqu+/E8wyCiIiI/Ep1EPTWW28hOTkZALBp0yZs2rQJX331Fe6//348+eSTbg9k7ty50Gg0SE9Pd/scRFTNGI1AdrYIXrKzxWNPjn/jDWDSJNPzK1eK7eZB0OTJooz2n3+KrJDBANx2m+V5GzUS2w0GICUF2L/flE0CgLVr1Y+ViIiIvEYjSeq6A4aFheG3335DcnIyJk+ejOLiYrz11lv47bffcOedd+IvJZ3TrezatQuDBw9GVFQUunXrhoXywmQXioqKEB0djcLCQkTJf5ElourBYBABiXkTUp1O9PyR1+CoPb5GDdM6IHtOnAD+90eg8nMMHGjbW0hJv6HYWGDZMmVjJSIiIpfUxAaqM0F16tTByZMnAQAbN25Ez549AQCSJMHoxl82L1++jOHDh+Ptt99GHS4WJiIl5ODDPIABgNxcsd1gcO94ZwEQAOzYIQKhxYuBBQuAcePsBztK/rZUUKBsrEREROR1qgsj6PV6DBs2DM2aNUNBQQHuv/9+AMC+ffvQtGlT1QOYMGECHnjgAfTs2RMvvvii031LSkpQUlJS/rioqEj16xFRJWc0mqakWZMkkYVJTwf69bMsSqDkeFcefxy4dEk0PvUGSXI+ViIiIvIJ1UFQZmYmUlJScPLkSbzyyiuI+F91pLy8PIwfP17VuVavXo09e/Zg165divafO3cuZs+erXbIRFSVbN9um8ExJ0nAyZPA66+Lqm2JiZZV2rKznR/vjPm6Hm85eVK8p7Q075+biIiI7FK9JshbTp48ifbt2+Obb75B69atAQBpaWlo06aNwzVB9jJBycnJXBNEVJ2sWgUMG6buGHmtECAqt8mlqgPFypXA0KH+HgUREVGlpmZNkKJM0Geffab4xR901DTQyu7du5Gfn4927dqVbzMajfj222+xePFilJSUQGs1PSQkJAQhISGKx0JEVVBiovpjcnOBAQO8PxZvcec9ERERkdsUZYJq1LCsn6DRaGB+mEajKb+vtDjCpUuXcPz4cYttjzzyCG6++WY8/fTTaNmypctzsDocUTVkNIqy07m57q3rqQhKqsPJ++l0QE4O1wQRERF5yOvV4crKysp/vvnmG7Rp0wZfffUVLl68iMLCQnz55Zdo27YtNm7cqHiQkZGRaNmypcVPrVq1EBsbqygAIqJqSqsVU8cCNQACRGCzfr34sW6kKpP/eLRwIQMgIiKiCqa6MEJ6ejqWLl2Ku+66q3zbvffei/DwcIwZMwa//vqrVwdIRGTBYABefdXfo7AVHw9kZgL161sWYujXD5gzR6xJMl+LpNOJAIh9goiIiCqcW81Sf/zxR7Rq1cpi+4EDB3DnnXfi2rVrXh2gM5wOR1TNyFPh3K3u5gtyRmfdOucBjdEoqsDl5dlWrCMiIiKP+bRZ6h133IH09HTk5eWVbztz5gymTZuGDh06qB8tEZFSrspj+4NO5zoAAkTAk5YmpvKlpTEAIiIi8iPV0+Heffdd6PV6NGzYEA0aNAAAnDhxAs2bN8enn37q7fEREZmY/fHFrxxNfSMiIqJKQXUQ1KxZM+zfvx+bN2/G4cOHIUkSbrnlFvTs2dOiShwRkdcdPerf15f/G7d0KdfyEBERVWKq1gSVlpYiNDQU+/btC4gKblwTRFSNGI1Aw4aiNLavaTRATAwQFmY5/S45mcUMiIiIApTXm6WW71yzJho2bKi4FxARkdds315xARAALFsmKruxmAEREVGVo3o63IwZMzB9+nR8+OGHiImJ8cWYiKgq8rQ6mq/WA8XFAefPmx5bl65OS/PN6xIREZHfqA6CXnvtNfz+++9ISkpCw4YNUatWLYvn9+zZ47XBEVEVYTAAkydbTi3T6UTvHKVTyxITfTO2zEwxFmZ7iIiIqg3VQVD//v19MAwiqrIMBmDgQMB6+WFurtiupLw0IIITnU4cp669mXOxscz2EBERVTOqm6UGEhZGIApwrpqbajQisMnJUZZ9cRRQeeKWW4ADB5j9ISIiquR82iyViEgxV81NJQk4eVLsp4ReLzJHwcGW22NjxY87Dh0C5swRARsRERFVC6qDIKPRiFdffRUdOnRAQkICYmJiLH6IiMopLWaQmwtkZwOrVolbZwGJXg8sXw6MHAm8+iqQlQWcPSt+srKAiRPVjzMjQ2SsDAb1xxIREVGlozoImj17NhYsWIDBgwejsLAQU6dOhV6vR40aNTBr1iwfDJGIKi2lxQymTAG6dQOGDRO3CQlim6OAaNgwYMUKYNo0sZ5HqxU/aWnAgAHujfXUKTHVjoEQERFRlad6TVCTJk3w2muv4YEHHkBkZCT27dtXvm3nzp1YuXKlr8Zqg2uCiAKcvCbIk2IGaqvIuVqH5IzaNUpEREQUMHy6JujMmTNo1aoVACAiIgKFhYUAgD59+uA///mPG8MloipLqxUBDGBqQqrWqVMiu/Pxx+LxtWvAtm3A4cPOX9Od11O7RomIiIgqJdVBkE6nQ97/5vk3bdoU33zzDQBg165dCAkJ8e7oiKjyk4sZ1K9vuT0+Xt15hg4V5/njDzHtLTXV9WvqdKqHC8B3jVmJiIgoIKgOgv72t79hy5YtAIDJkyfj+eefR7NmzfD3v/8do0eP9voAiagK0OuBY8dMj3U60aRUDaMRGDQIkNcexsUpe82sLCA9Xd1r+aoxKxEREQUEj/sE/fDDD/juu+/QtGlTPPjgg94alyJcE0RUiUgSUON/f3fR6YAPPhBFENwVHCyqySldK2QwAJMmifVJjnBNEBERUaWlJjZgs1Qiqhg3bpj6+8TEAPn5QL16QEGBZ+ddv15d0YQ5c0RJbGvyGqJ165Sfj4iIiAKGTwsjJCUlYdiwYVi2bBmOHDni9iCJqJq5ds3y/oYNngdAADBmjPJGp1otMHOmCJys1wvpdAyAiIiIqgnVQdD8+fMRFRWFBQsWoEWLFkhMTMRDDz2EpUuX4tdff/XFGImoKggLE0EGAHTpAowb553zFhSI7I4a5uuFVq4Utzk5DICIiIiqCY+mw509exZZWVn44osvsGbNGpSVlcGo9C+yXsDpcESVkMEAjB0LnD/vvXPGxgJnz3IdDxERUTWmJjao6c4LXL58GTt27MC2bduQnZ2NvXv3olWrVujatatbAyaiasJgAAYOdL9xqiMFBaK3T1qad89LREREVZLqIOjOO+/EgQMH0LJlS6SlpeHZZ59Famoqateu7YPhEVGVcfo08Oij3g+AZOztQ0RERAqpXhN09OhRhIeHo3HjxmjcuDGaNm3KAIiIXFu/Hrh40XfnZ28fIiIiUkh1EHThwgVkZWWhS5cu2Lx5M7p27YqEhAQMGTIES5cu9cUYiagq8FWmRqMBkpOB1FTfnJ+IiIiqHI/7BO3evRuLFy/Ghx9+yMIIROTYnDnAjBnePSd7+xAREdH/+LQwwt69e5GdnY3s7Gxs374dly5dQuvWrTF58mR086T7OxFVbY0be/+c9esDixYxACIiIiJVVAdBd9xxB26//XZ07doVjz32GO6++25mYYjIte++8/45V6wAevTw/nmJiIioSlMdBF24cIFBDxGpYzQCH33k/fPm53v/nERERFTlqS6MEBUVhYsXL+Kdd97B9OnTceHCBQDAnj17kJub6/UBElEVsH27byrDsSIcERERuUF1JujAgQPo0aMHateujWPHjuGxxx5DTEwMPvnkExw/fhzvv/++L8ZJRJWZ0spwMTHA//6w4pRGA+h0rAhHREREblEdBE2dOhWPPPIIXnnlFURGRpZvv//++zFs2DCvDo6IApzRKLI8eXkiK9O5M/D996bHqamAVqs8Y7N2rdg/Lw84ehSYNUtsNy9iKVeEW7hQ7EtERESkkuogaNeuXXjrrbdsttevXx9nzpzxyqCIqBIwGIDJk4FTp0zbtFoRGMl0OlG9rV8/cT831zKgMVe7NpCWZhnYtGxp+xo6nQiAWBGOiIiI3KQ6CAoNDUVRUZHN9iNHjiA+Pt4rgyKiAGcwAAMH2gY01n3CcnPFfuvWAePGiT5BGo39QGjwYNvMjl4vAijzbJOcXSIiIiJyk+rCCP369cMLL7yAGzduAAA0Gg1OnDiBZ555BgMGDPD6AIkowBiNIjujpM+yvE96OvDbb+K+o+qSjtb3aLUiQzR0qG2miIiIiMgNqoOgV199FefOnUPdunVx7do1dO3aFU2bNkVkZCTmzJnjizESUSDZvt1yeporkgScPCl+ALHOJytLZIbMRUR4bYhEREREzqieDhcVFYUdO3Zg69at2LNnD8rKytC2bVv07NnTF+MjokCjtNKbtcJCcVurlsjoXLgALF0qtnXvDiQleWV4RERERK6oCoJKS0sRGhqKffv2oXv37ujevbuvxkVEgcrd3jxyVbewMHErV5ds2RLYssXzcREREREppGo6XM2aNdGwYUMYrRc/E1H1kZoqKrTJQY0rGg2QnAyEhIjH1kHQpUveHyMRERGRE6rXBM2YMQPTp0/HBSUNDYmo6tFqRdlrwHUgZN7Tp7hY3GcQRERERH6mOgh67bXXsH37diQlJeGmm25C27ZtLX6IqBrQ60XZa+uy+NaV23Q6sZ9eD1y7JrZZB0EXLgCxscD5874dMxEREdH/qC6M0L9/fx8Mg4gqHb1eNDjt0UM87tED+PJL4KWXgK1bRfGDjAxTYLRokQh0br1VPJaDIEAEQuHhFTl6IiIiqsZUB0EZGRm+GAcRVUbXr5vul5QAX38NrFgB9OwJvPCC5b733GP5uHZtUwNUjcaUISIiIiLyMdXT4YiIyslT3ACgY0fR/+f4cWVT2zQa4MoVcb9WLeWFFoiIiIg8pDoTRERU7ttvTfdffdV0/8IF4Nw5yzVDq1YBoaHA/feLWwC4fFncslEqERERVSCNJEmSvwfhrqKiIkRHR6OwsBBRUVH+Hg5R9WIwAAMGOH4+Lk4EQoCYNieXyP70U6BPH7FWqH17YPdusb3y/qeIiIiIAoCa2IDT4YhIPaMRmDzZ+T4FBWI/gwFo3Ni0vX9/ICVFbJcDICIiIqIKxCCIiNTbvh04dcr5PpIE/N//AQMHArm5ls/l5ort8jqgsDAgO1sETUREREQ+pnpNkNFoxIoVK7Blyxbk5+ejrKzM4vmtW7d6bXBEFKDy8pTt99pr9qe5WW+7dg3o1k30FVq0SJTfJiIiIvIR1UHQ5MmTsWLFCjzwwANo2bIlNKzoRFR1GY0i65Obayp0UL8+ULeusuP/+kvd68kZIrnBKhEREZEPqC6MEBcXh/fffx+9e/f21ZgUY2EEIh8yGMS6H3vT3urXB4qLRRU4bxc00GhERignx9RolYiIiMgFnxZGCA4ORtOmTd0eHBFVAgaDyMg4WveTmysKH/iiopskASdPigwUERERkQ+oDoKmTZuGRYsWoRJX1iYiZ+TKb67+jWs0QFCQ78ahdN0RERERkUqq1wTt2LEDWVlZ+Oqrr3DrrbciyOoiyGAweG1wROQHSiq/ASJIunHDd+NITPTduYmIiKhaUx0E1a5dG3/72998MRYiCgQVkYHRah2Xw5bXBKWm+n4cREREVC2pDoKWL1/ui3EQkb/JleAOHfL9a6WnAwsWiPvm0+7kapMLF7IoAhEREfkMm6USkSiEkJIievW8+KJvX0ujAdauFT/161s+p9OxPDYRERH5nOpMEACsW7cOa9euxYkTJ3D9+nWL5/bs2eOVgRGRCnIWJy9PrKVJTVWeSZErwVVUsRO5+ltcHHDsmPvjJiIiInKT6kzQa6+9hkceeQR169bF3r170aFDB8TGxuLPP//E/fff74sxEpEz5lmcYcPEbUqK2O6K0kpwSqhtnJyXJwKetDRg6FBxywCIiIiIKoDqIGjJkiVYtmwZFi9ejODgYDz11FPYtGkTJk2ahMLCQl+MkYgccdTPJzdXbHcVCCmtBKeE2kCK1d+IiIjIT1QHQSdOnEDnzp0BAGFhYbh06RIA4OGHH8aqVau8OzoicsxZFkfelp7uuAobAGzY4N0xxcS43kejAZKTWf2NiIiI/EZ1EJSQkICCggIAQMOGDbFz504AQE5ODhuoElUkV1kcee3N9u32n79+HfB2tcfJk5VNi2P1NyIiIvIj1UFQ9+7d8fnnnwMAHn30UUyZMgX33HMPhgwZwv5BRBVJaT8fe/sZDKIymzensMbHA889BzzxhPP9nniC1d+IiIjIr1RXh1u2bBnKysoAAOPGjUNMTAx27NiBvn37Yty4cV4fIBE5oHRNjfV+vqoGN3y4uHU1LXb1amDuXGaCiIiIyG80UiWew1ZUVITo6GgUFhYiKirK38MhqlhGo6gCl5vrOKCJjwcyM0XWR16Dk5LivWII5rKyxG23bsr2TUvz/hiIiIio2lITG7jVLHX79u0YMWIEOnXqhNzcXADABx98gB07drhzOiJyh1YLLFok7jtah3PuHDBihKls9pw5vgmA5EIHnkzRIyIiIqogqoOg9evX495770VYWBj27t2LkpISAMClS5fw0ksveX2AROSEXg+sWwckJbneNzcXyMjwzTjkQgfuTtEjIiIiqkCqg6AXX3wRS5cuxdtvv42goKDy7Z07d8aePXu8OjgiUkCvB376yfTYUfrXVzNfa9UyFTpITQV0OseZKZbHJiIiogCgOgg6cuQI7r77bpvtUVFRuHjxojfGRERq/a9fF8LDgaKiinlN+Y8g0dGmbc6m6MmPWR6biIiI/Ex1EJSYmIjff//dZvuOHTvQuHFjrwyKiFSS/wARFub719JoxM8rrwB33QV06GD5vDxFr359y+06ndjO8thERETkZ6pLZI8dOxaTJ0/Gv//9b2g0Gpw+fRr//e9/8cQTT2DmzJm+GCMRuSIHQTVV/5NWT6cT2Ry9HkhPt7+PXg/06ycatebliTVAqanMABEREVFAUH3F9NRTT6GwsBDdunVDcXEx7r77boSEhOCJJ57AxIkTfTFGourLaFQWSPz1l7g9e1ZMibt2zf4aII3GlKFRWyUuIgL49FNR2lqrBU6fBr78UpyzSRPbsWm1LINNREREAcmtEtlz5szB+fPn8eOPP2Lnzp04d+4c/u///k/1eebOnYs77rgDkZGRqFu3Lvr3748jR464MySiqsdgEGWtu3UDhg0zlbk2GGz3NV+P166d/fPJa3IWLTKt21Hj8mWgsFAEN/LYHnsM+Mc/nI+NiIiIKMC4FQQBQHh4ONq3b48OHTogIiLCrXNs27YNEyZMwM6dO7Fp0yaUlpaiV69euHLlirvDIqoaDAZg4EDbbE1urthuHWyYB0F16wIffWR7TvM1OXo9MGCA7T41nPwnQaMR09/WrRNjuHFD2diIiIiIAoxGkpTVzR09erSiE/773/92ezDnzp1D3bp1sW3bNrsV6Kyp6QpLVGkYjSKr4mi6mkYjApqcHNP0s4sXgdmzxVqdvn2Bf/0LuPlm0zGbNolsjfl0tYkTgTfeEM1Ue/cWU+mmTHE9vvh40YRV6diIiIiIKoCa2EDxmqAVK1agYcOGuP3226EwblKtsLAQABATE2P3+ZKSkvLmrIB4o0RVzvbtztfrSBJw8qTYT15zU7s20LatuH/9unjeXOvWtkGJvI7o9tuBoUOBVauUjc9RAORobEREREQBRnEQNG7cOKxevRp//vknRo8ejREjRjgMVtwhSRKmTp2Ku+66Cy1btrS7z9y5czF79myvvSZRQMrLc2+/4GBxW1IiMj+y//wHiIwU980LLcil7uvUEbeJie6P2dXYiIiIiAKI4jVBS5YsQV5eHp5++ml8/vnnSE5OxuDBg/H11197JTM0ceJEHDhwAKuc/DV6+vTpKCwsLP85af3XbqKqQGkwYr7fsmXAyy+L+99/L3r4yMaOFVXcrAst/PijeP7wYXGbmiqmslk3OZVpNGIqnDffAxEREZEfKF4TZO348eNYsWIF3n//fdy4cQOHDh1yu0DC448/jk8//RTffvstGjVqpPg4rgmiKkleE5Sb67zM9YoVQH6+CDieeQb44Qf1ryUHPHLBBLkgA2D52vJ+a9YAU6c6HxvXBBEREZEfqIkN3K4Op9FooNFoIEkSysrK3DqHJEmYOHEiDAYDtm7dqioAIqqytFpTCWvrrIxGI4KPa9eAnj1NpbPlrI5aciCTni6CL71eBERyLyGZXFlu0CDnYwNEcQYGQERERBTAVAVBJSUlWLVqFe655x7cdNNNOHjwIBYvXowTJ064lQWaMGECPvzwQ6xcuRKRkZE4c+YMzpw5g2vXrqk+F1GlZDQC2dmiKEF2tngMOA5G5HV4BQWW2z2ZkmpezEB+7WPHgKwsYOVKcZuTI7Y7G5t5CW4iIiKiAKZ4Otz48eOxevVqNGjQAI888ghGjBiB2NhYz17cwdqD5cuXY9SoUS6P53Q4qtQMBmDyZMtKcHFxwJIlIuMCiKCo5v/ql8jT4JxVjvPEypWiSpxS5kUWEhPFmiJmgIiIiMhP1MQGioOgGjVqoEGDBrj99tsdBi8AYKjARokMgqjSktfeOPrn9+STpuIG8r+3mjWB0lLfjSkri2WtiYiIqNLySZ+gv//9706DHyJSyGgUGSBnf3/417+ADh1EoLR7N9CunShzLff28TatFjh/3jfnJiIiIgowbleHCwTMBFGllJ0tihm4Eh8vppr9+SfQvDkQHg5cveq7cWk0XNNDRERElVaFVIcjIjcpbSR67pxYcyP/I7561XkfH2+Qq8QRERERVWEMgogqmppGonv3ArffbnosN0T1BesqcURERERVFIMgooqWmiqqwCkRGmrKHN10E3DvvWLKmtLj3aE0U0VERERUSTEIIqpoWq0og+1KcjLQuLG436oVcPiwCH70euCNN3w3PjWZKiIiIqJKiEEQkT8MGiTKYDui0QALF5oKIVgv7isqsj3m2WeBTp2AevXcG5NGIwKv1FT3jiciIiKqJBgEEfnLK6+YmqKaq10bmDUL6NfPFOxERlruI5fKHjIEqPG/f8Zt2oj1PBkZ6sciF1tYuJANT4mIiKjKYxBE5E8JCeI2NdUUzFy8KAKZlBRTkYKNG4HbbgM2bRKP5SBowwagrEzcHzxYHHPunPpx6HQsj01ERETVhuJmqUTkAwUF4tZeRbbcXODdd02PDx4EzpwR93fvFrfFxbbHZGQAsbHAhQuOG7KGhAD/+Q+Qny/WAKWmMgNERERE1QaDICJ/eu01YOtWU3BjTg5gatQwZXuKikQfH0dlrOVj5OBIo7EfCN1xB9Cjh2djJyIiIqqkOB2OyJ/MszuOlJWJzA0AXLokAqBr15wfc+UK0LQpUL++/edbtFA/ViIiIqIqgpkgIn9S2pOnpETc7toFNGyo7Jg6dYBffxVBU14eEBwMbN4MLF1qW2iBiIiIqBphEETkTwaDuv2/+QYYP17ZvtHRYp1PWppp25Yt4jYiQt3rEhEREVUhnA5H5C+lpaIiG2AqUe3K5cviNibG9b72MkaXLolbZoKIiIioGmMQROQvFy64d1xWlqlEtrPgyTrb88orwIcfivuxse69NhEREVEVwCCIyF/y88VteLhojhoXp+y4OXNMFd+sg5ngYNP9sDDL5zZsELfr1wOPPKJ6uERERERVBdcEESkll6bOy1PfW8f62PPnTWt7rl4VvX2SksT5jEblYzp/XgRPI0YA/fqJNUavvy6eCw+33DcqStwWFSk/PxEREVEVxCCISAmDAZg8GTh1yrRNpwMWLQL0evXH2pOX57i5qTMFBWIcqami79B994lmql27Wu4nrwOS1wURERERVVMaSXLnqiswFBUVITo6GoWFhYiS/8pN5G0GAzBwoG2AIq/HWbfOcSDk6Fhv02hEUJaT4zg79eijwL//Le4fOQI0b+7bMRERERFVIDWxAdcEETljNIosjr0gRt6Wnm5/CpuzY71NkoCTJ8WUO0fM/2NQVub7MREREREFKAZBRM5s3+58Gpuz4MPVsb4we7bICo0dazvtzbwsNvsEERERUTXGIIjImbw89/dTeqw3BQWJ22XLRCltczXNlgDu26euAAMRERFRFcIgiMiZxET391N6rDdoNEByslgXJDOvDmcwAG++aXrcty+QkiK2ExEREVUzDIKInElNFYGFo6akcvCRmqr+WG9buNCyN5B8Xy7OcOaM5f65uWI7AyEiIiKqZhgEETmj1Yry04BtMCM/XrjQfkU282N9bdYsUaHOvFlqeLhnhR2IiIiIqigGQUSu6PWiDHZSkuV2nc55eWxZTIzvxiZr1kzcmgdBYWGeFXYgIiIiqqLYLJVICb0e6NdPBAt5eWK9T2qq4548gLoeQVqtKFvtbjltef2RdSbIk8IORERERFUUgyAipZ58EoiLAyZOtOy5Y4/aHkHydDSNRl0gJDdJldckNWxoei4szLPCDkRERERVFIMgIiWuXAEyM8X9xx4TQYuzLJA7PYLS08X0OvPjkpOBhx4CXn1VPDYPkOytSRo1Shx/7ZroCyQXZ8jNtR9cWQdRRERERNUA1wQRuWI0WlZQq1sX2LnT+THuTC/r1w84dkz091m5Utzm5ACvvCKCo/r1Lfe3tyapZk1RJGHePCA01LPCDkRERERVFDNBRM4YDGJam3VWZ+NGoEsXx8f99pvy1zDPxmi1QFqa7T5K1yQZjbb7yIUdrN+HTicCIFeFHYiIiIiqGI0kubsS2/+KiooQHR2NwsJCRLlao0GklqvCBuvXWwYQcgDyySfA668rX9uj0SirMqdkvP/4B/DXX6ZtOp3IBOn19gMkZoCIiIioilATGzAIIrLHaARSUpyv60lOFtPVtFrHGSNXkpO9k41xFLDJU968EWQRERERBTA1sQHXBBHZo6SwgdxfRw5A1AZAM2aIIMrT4IQNUYmIiIhUYRBEZI/Swga5uepKYZv78kvgrbfUH2eNDVGJiIiIVGEQRGSP0r45586pzwDJ9uwxld32BBuiEhEREanCIIjIHrm/jnVZaXPJyUB8vGevExHh2fEAG6ISERERqcQgiMgeV/11NBpR0MC6d4+S83bsaHrsjSDIVcCm0YiAjQ1RiYiIiAAwCCJyTO6vU7eu5XbzJqVKMkbmVq0CWrUyPfZGEMSGqERERESqMAgickavB158Udxv2RLIyhIV3fr1E9ucBSDmkpNFX6FBg4A6dUzbIyO9N85162wzU+YBGxEREREBAGr6ewBEAc1oBLKzxf1GjYCzZ4GwMJEBev55U+PRtWuBceOAggLTsfHxwPDhImAyb0xqHgR5IxMk0+vFa7EhKhEREZFTDIKIHLFugPr558D33wM3bgA7dgDdupn21emA++4DPvpIPL7nHuCrr+wHIE2amO57MwgCxOulpXn3nERERERVjEaS3GlwEhjUdIUlUkVugOruPw+dDnjsMbH+529/s33+zBngxAkgNtYyKCIiIiIit6iJDRgEEVkzGoGUFPf7/5jT68VaICIiIiLyKTWxAafDEVnbvt07ARAA/PWX7Tajket2iIiIiPyIQZA38KI28D8DNePLy/Pe6+7aJV5bfi2DAZg40fI1dDpRYY4V3IiIiIgqBEtke8pgEFOnunUDhg0TtykpYnt1EeifgdrxJSZ677UvXxbBlzyOgQNtg6zcXLE9UD4vIiIioiqOQZAn5Ita66lT1emiNtA/A3fGd+6cd8eQlyeyQZMn2y+0IG9LTxf7EREREZFPsTCCu1wtntdoxDSnnBwxFSrQp4u5Q+1nUNHcGZ83iyLIsrLErXlJbWf7ssQ1ERERkWpqYgNmgtzlavG8JAEnT4r91EzHkptzrlolbgM5M6DmM/AHd8bnzaIIgCiBnZqqfJ2RN9cjEREREZFdDILcpfRi9Y03gAEDlE3HCvS1NdYC/cLenfF5e6z/+pfIMildZ+TN9UhEREREZBeDIHcpvVhdt87+dut1IIG+tsaeQL+wd2d83hzrnDnAI4+I+6mpYuqdRmN/X40GSE4W+xERERGRTzEIcperi1ol5OlY2dmVc9F8oF/Yy+NzxN74PP29xsQACQnifps2pu1arSiDLb+u9TgAYOHCyr9OjIiIiKgSYBDkLmcXtWplZwf22hpHvH1h7+31UBs2ANeu2X/O0fjM35Na0dHA0qXAzTeLxy+8YPn6er3IDNavb3mcTie2s08QERERUYVgEOQJRxe1vhKIi+blzyAuznK72gt7V+uh1AZI8vTCggL7z8fEiPH162d7Xvk9qQ1ui4qAIUOACxfE4x9+sB2nXg8cOyaqwK1cKW5zchgAEREREVUglsj2BqMR+PhjYOhQUzlsJeQSzcuXAz17ut4/kMsnf/AB8Pe/i/stWgAHDyrPAMkBi/VXUQ5CnnhCBCnm2TKdTmRs+vWzLT0OuC5zHRcHDB8uAhHzvkBxccCSJUDfvkBYmNj29tvA6dPArFn2pyxaj7lOHVMgtHUrcPfdnOZGRERE5GNqYgMGQd5y/ToQEqLuGI3GlI1ISRFFEOz9Ovzdb0eJefOAZ54R9++4A/jxR2XHuduXR6MRn1VsrGW2R6cDHnsMyMhQdz5r48cDX3wBXLwofjQaEayNHQucP6/uXHLAxmwPERERkc+wT5A/BAcDdesCNWoA9eq5nkplPl3M2ToUTxfNV1TfodxccfvUU8oDIMD9vjxysGg93e3UKc8DIEBkg+bPNwVAgPhdLVyo/lyBXOGPiIiIqBpiEORNP/8sMkJLlojHjgKhadPEuhDzzIAvFs1XVN8hoxHYt0/cLy5WF2gF4jon2fjxQFmZ5TZ31n8FcoU/IiIiomqIQZA3xcSIzEZJiVg/Yu+CuW9f4NVX7Wd19Hrg+HHvLJqvqL5DcqAlV6577TV1gVYgNwc9d862Ip+7JbQDtcIfERERUTXEIMhbrLMuGRniwnf2bBHQ9O0r9mvb1vl5NBrg5ZdFNqlNG/enwFVE3yFHgdapU8oDLW/0W/Kll1+2/Jw8LY0eyJkvIiIiomqCQZA3OMu6ZGSI3jFbtohtv/0msj2OzJkDfP01sGOHKLmslPnan9df933fIWeBlsxZoCWPd+1aUcgACMxA6OuvbTNbnpRGD+TMFxEREVE1wepwnnKnutkzzwBz59p/rnFjMQUOAA4dEuWmHb2uXBr66FFRxlltgYGVK0VZb3dkZ4uslyv2ynobDCKAMh9vbKxYf/PXX6ZtycnAQw+J6YOA6/LUroSFOW6e6owcnFmvzTL/HdStC4waVbkr/BERERFVYmpig5oVNKaqy53qZhcvKnvu8mX7+9gLItzhSVZC6bQu6/0c9QS6cMFym14vskRaLdCxIzBpkqkCHWAqjS2XylZi+HDgnXeU7WtOksTrpKeLcuZyEKPVWgZ4ixaJ92Y9Jk8r/BERERGRV3E6nKfcWeNhnu0wV1YGFBaaHl+5YruPo6l3amg0IssiNxZ1h9IAynw/JWuVZHXqmAIGuWDEmjVAy5YiKDp7Fli/XhSjUCI0VExLXL9eZGTM1VDwz0DJFEJfVPgjIiIiIq9jJshT7mRTLlwQ08ny8sTxqanigv/SJcuSzNZBkJJ1OK7Yy0qYT+syH48zckEDR9O/ACA+Hujc2fRYTdbMOgum1QJ33SXKkGu1pvdx4YKy873/vjhOrxfZnKwsUf0tMVGMsWNHYO9e1+dxFfTK51f7eRIRERFRhWEQ5KnUVJGNUHIxPm2aaMCZnQ1s2mTartOJqVTt2lnubx0EudtY1FxMDPDmm+J21Sr764nk8TjLXMhV0gYOdLzPuXNAkyamc6nJmtnLgsXHi1ujEfjkE2DMGOUB4dSppmO//hpo3Rp4/HFTcKIkGwQoC3qtp8kRERERUUBhEOQprVZkZzIyXO8rT4O7ccNyu9y7Ry4AAADh4UBpqeV+3iivfP06MGWK5foaa/J4XE3hkqd/PfwwcPWq63OpyZpZZ4J27gReecX02FnwZc+pU8DgwZbbZswAgoOBQYOAI0dcn0On82wKIREREREFBFaH8wajEahXTyzUd0SrBeLixFoWezQakenIzwduugk4fNh2H6UV2bxBTTWztDRg2zbX5/r9d5EZclZBLSkJ+PJL8VklJZme+/BDEWz50+zZwMyZ/h0DEREREdmlJjZgYQRv0GqBZcuc97mpV89xAASIoCA/X0xR+/xz+/tUZGNRNb2Efv9d2bm+/95xo1G5olrXriJTZh4AAc4DzIrSrJm/R0BEREREXsAgyFvkqWHWlceSk0WAdPq0svNIkuOLbXkdTkUyn4Jn3pA1O1s8liSx9kfpuZxVULvzTtG76IcfbI/dt8/NN+BFbHRKREREVCX4PQhasmQJGjVqhNDQULRr1w7blWQeApVeDxw7JiqPffAB8NlnYjqZmgadhw6JtSq9ewOvv24bdDgKtkJCvPhGzMgX/gaDaArbrRswbJi4TUkBVq8GmjZVdy75c/roI+Ddd8XnlZMjmpkCwOLFtmus9u/3wptxkzdKihMRERFRwPDrmqA1a9bg4YcfxpIlS9ClSxe89dZbeOedd3Do0CE0aNDA5fEBsybI2tatQM+eQIsWIoNRq5ZtMQQlQkKAkhLTY/OqbdZlrV94QQQT3qTTiWBlwwb7DU6Vsre+6J//FFXaXngBGDFCbGvdGjhwQNwPDja9d6NRfIbmn0VFkaftsc8PERERUUCrNGuCFixYgEcffRT/+Mc/0KJFCyxcuBDJycl488037e5fUlKCoqIii5+AFBsrAoZDh4CoKPcCIMD2ol+utGYwmMowDxgg1tHIU9LUVk1z5tFHRQbqscc8C4AAy75EgHgvOTkiw7NqFbBli+WUwevXTZ/b9u3+CYAANjolIiIiqoL8FgRdv34du3fvRq9evSy29+rVC99//73dY+bOnYvo6Ojyn+Tk5IoYqnr16pnuFxd777xyIDJ5slg3pNGIbNGFC8CJE+K5detM+3taQOH110VGS2lDUnscBRHHjonbV18V0+t69gTOn7fcZ/VqceuN0uDumj+fARARERFRFeO3IOj8+fMwGo2oZx4wAKhXrx7OnDlj95jp06ejsLCw/OfkyZMVMVT14uJ8d25JEj1vzCuyrVkD2MuKeTrT0ZPgBwBefFFke6yDCIMBOHjQ9fF//7voaaS0qIS3aTSiwa3R6J/XJyIiIiKf8HuzVI1VtkKSJJttspCQEIT4qgCAN9Ws4I/VVaNWrdY/F/KRkbY9hoxGkclSauFC5fvKZbYd0enE1L6//hJFGVxVtTMvE56WpnwcRERERBTQ/JYJiouLg1artcn65Ofn22SHyAXraWTW5GauADB8uO/HI6tVy3bb9u0ik+VtgwbZL7s9e7You52VJabgzZwJZGaKKXYzZig7tz+n4xERERGR1/ktCAoODka7du2wadMmi+2bNm1C586d/TQqL/n4Y9+ePyJC/TFyhYybbvLuWJxp3tx2m68CivR0U3ly66Bn6FCRyTHPSmm1QI8eys7N/kBEREREVYpfp8NNnToVDz/8MNq3b49OnTph2bJlOHHiBMaNG+fPYXnGYAAGD/bta1y+rP6Y2rXFrU4n+vGo6V2khjyVce1aU18d83LeZ8/65nUjIkwV85RKTRWfR26u/Wl0cmlv9gciIiIiqlL8GgQNGTIEBQUFeOGFF5CXl4eWLVviyy+/RMOGDf05LPepXe9SEeQL+YYNgV27RADVuDHwyy+Oj7HuT6SGTifW8cjFEAwG8ZmYT4GrUQMoK3Pv/I7Ym3rnilYr+i4NHGi7nshRaW8iIiIiqvT82icIAMaPH49jx46hpKQEu3fvxt133+3vIbnPV+td3GV+IS9ngoqKTAGIdRU7eX9HAZCSktvmJaXXrRN9jKw/E28HQIB7QRAgxrpunf31ROwPRERERFQl+b06XJUSaAvo4+KApUvFhfx334ltFy+agpKXXwZSUoAvvhCBkquS2pGR9ktxy+SS0hcvAv/+N/Djj56/B2evZT5ed4MgQHw+/fqZpuwlJoopcMwAEREREVVJDIK8KdAW0GdmmjIZ0dHi9s03gStXxP1//ENkQJQ2dHUWAAGmktLvvOPbAEh+LXPh4Z6dT+16IiIiIiKqtPw+Ha5KkRfaK5k2VhHMp3g1aSLGJQdAstxcoKDAu6974ID7xyr97GJjTfdHj2bWhoiIiIgUYxDkTfJCe8C/gZBGAyQnW1Zne+YZ19PdvEVpZsmemBggKMj1fgUFpilwTz/t/usRERERUbXDIMjbHC20T04WZaN9nSmyV9Wsogo2aDQiiHHHxImisemFC8CNG8qOefhh4KOPgLp13XtNIiIiIqqWGAT5gl5v27gzJwcYNMj3mSJ7Vc0qomCD/H7cLRHevz/w9tvqslV9+gC33WY7xY+IiIiIyAkGQb4iL7QfOlTcylkZZyWZY2PdD45uvhnYvFkEW9ZlnSuiYIMcfD33HBAVpfw4eeoeoDxbJR9TXAy0agXcfTeQnS2m/RERERERucAgyB/sZYqOHQOWLRPPuxMIHT4MjBoFbNhg+1xqKlCvngcDdiAz0zLTpdeLYK9XL3XnWbgQyM9Xd8xDDwGPPCLu//kn0K2bKPdtMKg7DxERERFVOxpJqqjV8t5XVFSE6OhoFBYWIkpN9iGQGQxiSpk7a3jk4Mlek8+33wbGjLF/jCSJLNSFC8qmo2k0IvOTk2O/KtvmzcA997g+T3AwsGqVGGt2tghkXImPF8Heq6/ajtXZ+yciIiKiKk1NbMAgKBAZjaKYwYYNIkti3RjUGUcBSlGRqVeQueRk8RoAMHCguFXyWuvXOw40rl8XxQoKCx0fHx0tsj/BweKx0SgyObm5jl8/Ph44fhxo3txxkOgqQCMiIiKiKklNbMDpcIFIXk+UmSmCDev1Q87IDUu3b7fcHhFh+fjf/7acxuZorZK9QCIjw3EAZDCInkTOAiCNBliyxBQAya/jqGiERiN+li4FfvjBeZbM0fsnIiIiIvofBkGBznr90IwZyo6zrghnnV35+98tCzbYe62sLODqVXGbkGDaLzHRfhECg0Fkk5wFKcnJItgaNsz2OWdFI+Qpbkor3VVERTwiIiIiqpQYBFUG5pXmevRQdox5RTiDQUw1M+eoiIB1VbvgYLFW6OJF0z7jxtkebzSKtUzOptLFxwO//y4anbZtC8yda7uPo/LicuZJaaW7iqiIR0RERESVEtcEVTau1s5Yr4mRszPuFhFQerzSwgZLl4rGqKWlwIQJwOLFro8xp/b9ExEREVG1wDVBVZmrtTOAKHSg1TrPzsjb0tMd99dRc7zS6WfffScCIAAID1d2jDk175+IiIiIyA4GQZWRkrUzgCgO4EkRATXHK51+JjdGBYCwMGXHWFP6/omIiIiI7Kjp7wGQm/R6oF8/EYDk5YkgJDXVMgPiaREBNccPHiyCEFfT1Lp0MW1zJxMkU/L+iYiIiIjsYBBUmclFDBzxtIiAmuPlaWoDB9r2NTKfphYba9p+6pSYSudu4OLq/RMRERER2cHpcFVZaqrIvlivnZFpNGJ6Wmqqd453NU0NAPr3N21fvNhxlToiIiIiIh9hEFSVeVpEwJ3jHZW4BkSW6MwZy/Pk5ortDISIiIiIqIKwRHZ1YDCIKm/mRQ6Sk0UAo6SIgKfHy2WtHRVZYFlrIiIiIvKQmtiAQVB1YTR6VkTAk+OV9hDKyuIaHyIiIiJyi5rYgIURqgtPiwh4crynVeqIiIiIiLyIa4LI9zytUkdERERE5EUMgsj3PK1SR0RERETkRQyCyPc8rVJHRERERORFDIKoYrjqIaSkyhwRERERkRewMAJVHL0e6NfPsyp1REREREQeYhBEFcvTKnVERERERB7idDgiIiIiIqpWGAQREREREVG1wiCIiIiIiIiqFQZBRERERERUrTAIIiIiIiKiaoVBEBERERERVSsMgoiIiIiIqFphEERERERERNUKgyAiIiIiIqpWGAQREREREVG1UtPfA/CEJEkAgKKiIj+PhIiIiIiI/EmOCeQYwZlKHQRdunQJAJCcnOznkRARERERUSC4dOkSoqOjne6jkZSESgGqrKwMp0+fRmRkJDQajV/HUlRUhOTkZJw8eRJRUVF+HQtVHvzekFr8zpBa/M6QWvzOkFqB8p2RJAmXLl1CUlISatRwvuqnUmeCatSoAZ1O5+9hWIiKiuJ/MEg1fm9ILX5nSC1+Z0gtfmdIrUD4zrjKAMlYGIGIiIiIiKoVBkFERERERFStMAjykpCQEGRkZCAkJMTfQ6FKhN8bUovfGVKL3xlSi98ZUqsyfmcqdWEEIiIiIiIitZgJIiIiIiKiaoVBEBERERERVSsMgoiIiIiIqFphEERERERERNUKgyAvWbJkCRo1aoTQ0FC0a9cO27dv9/eQyE++/fZb9O3bF0lJSdBoNPj0008tnpckCbNmzUJSUhLCwsKQlpaGX375xWKfkpISPP7444iLi0OtWrXw4IMP4tSpUxX4LqiizJ07F3fccQciIyNRt25d9O/fH0eOHLHYh98Zsvbmm2/itttuK29M2KlTJ3z11Vflz/M7Q67MnTsXGo0G6enp5dv4vSFzs2bNgkajsfhJSEgof76yf18YBHnBmjVrkJ6ejueeew579+5Famoq7r//fpw4ccLfQyM/uHLlClq3bo3Fixfbff6VV17BggULsHjxYuzatQsJCQm45557cOnSpfJ90tPT8cknn2D16tXYsWMHLl++jD59+sBoNFbU26AKsm3bNkyYMAE7d+7Epk2bUFpail69euHKlSvl+/A7Q9Z0Oh1efvll/PTTT/jpp5/QvXt39OvXr/wChN8ZcmbXrl1YtmwZbrvtNovt/N6QtVtvvRV5eXnlPwcPHix/rtJ/XyTyWIcOHaRx48ZZbLv55pulZ555xk8jokABQPrkk0/KH5eVlUkJCQnSyy+/XL6tuLhYio6OlpYuXSpJkiRdvHhRCgoKklavXl2+T25urlSjRg1p48aNFTZ28o/8/HwJgLRt2zZJkvidIeXq1KkjvfPOO/zOkFOXLl2SmjVrJm3atEnq2rWrNHnyZEmS+N8aspWRkSG1bt3a7nNV4fvCTJCHrl+/jt27d6NXr14W23v16oXvv//eT6OiQJWTk4MzZ85YfF9CQkLQtWvX8u/L7t27cePGDYt9kpKS0LJlS36nqoHCwkIAQExMDAB+Z8g1o9GI1atX48qVK+jUqRO/M+TUhAkT8MADD6Bnz54W2/m9IXuOHj2KpKQkNGrUCA899BD+/PNPAFXj+1LT3wOo7M6fPw+j0Yh69epZbK9Xrx7OnDnjp1FRoJK/E/a+L8ePHy/fJzg4GHXq1LHZh9+pqk2SJEydOhV33XUXWrZsCYDfGXLs4MGD6NSpE4qLixEREYFPPvkEt9xyS/nFBb8zZG316tXYs2cPdu3aZfMc/1tD1u688068//77aN68Oc6ePYsXX3wRnTt3xi+//FIlvi8MgrxEo9FYPJYkyWYbkcyd7wu/U1XfxIkTceDAAezYscPmOX5nyNpNN92Effv24eLFi1i/fj1GjhyJbdu2lT/P7wyZO3nyJCZPnoxvvvkGoaGhDvfj94Zk999/f/n9Vq1aoVOnTmjSpAnee+89dOzYEUDl/r5wOpyH4uLioNVqbSLa/Px8m+iYSK6q4uz7kpCQgOvXr+Ovv/5yuA9VPY8//jg+++wzZGVlQafTlW/nd4YcCQ4ORtOmTdG+fXvMnTsXrVu3xqJFi/idIbt2796N/Px8tGvXDjVr1kTNmjWxbds2vPbaa6hZs2b5753fG3KkVq1aaNWqFY4ePVol/jvDIMhDwcHBaNeuHTZt2mSxfdOmTejcubOfRkWBqlGjRkhISLD4vly/fh3btm0r/760a9cOQUFBFvvk5eXh559/5neqCpIkCRMnToTBYMDWrVvRqFEji+f5nSGlJElCSUkJvzNkV48ePXDw4EHs27ev/Kd9+/YYPnw49u3bh8aNG/N7Q06VlJTg119/RWJiYtX474w/qjFUNatXr5aCgoKkd999Vzp06JCUnp4u1apVSzp27Ji/h0Z+cOnSJWnv3r3S3r17JQDSggULpL1790rHjx+XJEmSXn75ZSk6OloyGAzSwYMHpaFDh0qJiYlSUVFR+TnGjRsn6XQ6afPmzdKePXuk7t27S61bt5ZKS0v99bbIR/75z39K0dHRUnZ2tpSXl1f+c/Xq1fJ9+J0ha9OnT5e+/fZbKScnRzpw4ID07LPPSjVq1JC++eYbSZL4nSFlzKvDSRK/N2Rp2rRpUnZ2tvTnn39KO3fulPr06SNFRkaWX99W9u8LgyAveeONN6SGDRtKwcHBUtu2bcvL21L1k5WVJQGw+Rk5cqQkSaKsZEZGhpSQkCCFhIRId999t3Tw4EGLc1y7dk2aOHGiFBMTI4WFhUl9+vSRTpw44Yd3Q75m77sCQFq+fHn5PvzOkLXRo0eX/z8nPj5e6tGjR3kAJEn8zpAy1kEQvzdkbsiQIVJiYqIUFBQkJSUlSXq9Xvrll1/Kn6/s3xeNJEmSf3JQREREREREFY9rgoiIiIiIqFphEERERERERNUKgyAiIiIiIqpWGAQREREREVG1wiCIiIiIiIiqFQZBRERERERUrTAIIiIiIiKiaoVBEBERERERVSsMgoiIyC8OHz6Mjh07IjQ0FG3atFF8XHZ2NjQaDS5evOizsRERUdXGIIiIiJw6d+4cgoKCcPXqVZSWlqJWrVo4ceKEx+fNyMhArVq1cOTIEWzZssXuPmlpaUhPT/f4tTw1a9YsVYEaEREFNgZBRETk1H//+1+0adMG4eHh2L17N2JiYtCgQQOPz/vHH3/grrvuQsOGDREbG+uFkRIRESnDIIiIiJz6/vvv0aVLFwDAjh07yu87U1ZWhhdeeAE6nQ4hISFo06YNNm7cWP68RqPB7t278cILL0Cj0WDWrFk25xg1ahS2bduGRYsWQaPRQKPR4NixY+XP7969G+3bt0d4eDg6d+6MI0eOWBz/+eefo127dggNDUXjxo0xe/ZslJaWOhxzdnY2OnTogFq1aqF27dro0qULjh8/jhUrVmD27NnYv39/+ThWrFgBACgsLMSYMWNQt25dREVFoXv37ti/f3/5OeUM0ltvvYXk5GSEh4dj0KBBnMpHRORvEhERkZXjx49L0dHRUnR0tBQUFCSFhoZK0dHRUnBwsBQSEiJFR0dL//znPx0ev2DBAikqKkpatWqVdPjwYempp56SgoKCpN9++02SJEnKy8uTbr31VmnatGlSXl6edOnSJZtzXLx4UerUqZP02GOPSXl5eVJeXp5UWloqZWVlSQCkO++8U8rOzpZ++eUXKTU1VercuXP5sRs3bpSioqKkFStWSH/88Yf0zTffSCkpKdKsWbPsjvfGjRtSdHS09MQTT0i///67dOjQIWnFihXS8ePHpatXr0rTpk2Tbr311vJxXL16VSorK5O6dOki9e3bV9q1a5f022+/SdOmTZNiY2OlgoICSZIkKSMjQ6pVq5bUvXt3ae/evdK2bdukpk2bSsOGDfPk10NERB5iEERERDZu3Lgh5eTkSPv375eCgoKkffv2Sb///rsUEREhbdu2TcrJyZHOnTvn8PikpCRpzpw5FtvuuOMOafz48eWPW7duLWVkZDgdR9euXaXJkydbbJODoM2bN5dv+89//iMBkK5duyZJkiSlpqZKL730ksVxH3zwgZSYmGj3dQoKCiQAUnZ2tt3nMzIypNatW1ts27JlixQVFSUVFxdbbG/SpIn01ltvlR+n1WqlkydPlj//1VdfSTVq1JDy8vIcv3EiIvKpmv7NQxERUSCqWbMmUlJSsHbtWtxxxx1o3bo1vvvuO9SrVw93332302OLiopw+vRpm2lzXbp0sZgq5qnbbrut/H5iYiIAID8/Hw0aNMDu3buxa9cuzJkzp3wfo9GI4uJiXL16FeHh4RbniomJwahRo3DvvffinnvuQc+ePTF48ODy89qze/duXL582WY907Vr1/DHH3+UP27QoAF0Ol35406dOqGsrAxHjhxBQkKCe2+eiIg8wiCIiIhs3HrrrTh+/Dhu3LiBsrIyREREoLS0FKWlpYiIiEDDhg3xyy+/OD2HRqOxeCxJks02TwQFBdm8VllZWfnt7NmzodfrbY4LDQ21e77ly5dj0qRJ2LhxI9asWYMZM2Zg06ZN6Nixo939y8rKkJiYiOzsbJvnateu7XDc8li9+VkQEZE6DIKIiMjGl19+iRs3bqBHjx545ZVX0K5dOzz00EMYNWoU7rvvPosAxFpUVBSSkpKwY8cOi6zR999/jw4dOqgaR3BwMIxGo+rxt23bFkeOHEHTpk1VHXf77bfj9ttvx/Tp09GpUyesXLkSHTt2tDuOtm3b4syZM+VZM0dOnDiB06dPIykpCYCotlejRg00b95c9fsiIiLvYBBEREQ2GjZsiDNnzuDs2bPo168fatSogUOHDkGv15dfzDvz5JNPIiMjA02aNEGbNm2wfPly7Nu3Dx999JGqcaSkpOCHH37AsWPHEBERgZiYGEXHzZw5E3369EFycjIGDRqEGjVq4MCBAzh48CBefPFFm/1zcnKwbNkyPPjgg0hKSsKRI0fw22+/4e9//3v5OHJycrBv3z7odDpERkaiZ8+e6NSpE/r374958+bhpptuwunTp/Hll1+if//+aN++PQCReRo5ciReffVVFBUVYdKkSRg8eDCnwhER+RFLZBMRkV3Z2dm44447EBoaih9++AH169dXFAABwKRJkzBt2jRMmzYNrVq1wsaNG/HZZ5+hWbNmqsbwxBNPQKvV4pZbbkF8fLziJq333nsvvvjiC2zatAl33HEHOnbsiAULFqBhw4Z29w8PD8fhw4cxYMAANG/eHGPGjMHEiRMxduxYAMCAAQNw3333oVu3boiPj8eqVaug0Wjw5Zdf4u6778bo0aPRvHlzPPTQQzh27Bjq1atXfu6mTZtCr9ejd+/e6NWrF1q2bIklS5ao+hyIiMi7NJIkSf4eBBERUVU0a9YsfPrpp9i3b5+/h0JERGaYCSIiIiIiomqFQRAREREREVUrnA5HRERERETVCjNBRERERERUrTAIIiIiIiKiaoVBEBERERERVSsMgoiIiIiIqFphEERERERERNUKgyAiIiIiIqpWGAQREREREVG1wiCIiIiIiIiqlf8HYtaLeFs2d4oAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "monte_carlo_rl_player = MonteCarloRLPlayer()\n",
    "monte_carlo_rl_player.load('trained_agents/monte_carlo_rl.pkl')\n",
    "plot_training_stats(monte_carlo_rl_player.rewards, len(monte_carlo_rl_player._state_values) step_size=1_000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Considering the above plot, we can see that the player is able to learn because of the implemented symmetries. Without the symmetries, the number of states is too large and the player would need a huge amount of matches to achieve the same learning performance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train MinMax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  0%|          | 0/100 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Found states: 5,262,427: 100%|██████████| 100/100 [22:58<00:00, 13.78s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New found states after 100 games: 5,262,427\n"
     ]
    }
   ],
   "source": [
    "minmax_player = MinMaxPlayer(depth=3, enhance=True)\n",
    "minmax_player.train(n_games=100)\n",
    "minmax_player.save('trained_agents/minmax_depth3_player.pkl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train AlphaBetaMinMax"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Found states: 3,467,383: 100%|██████████| 20/20 [27:21<00:00, 82.05s/it]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "New found states after 20 games: 3,467,383\n"
     ]
    }
   ],
   "source": [
    "alphabeta_minmax_player = AlphaBetaMinMaxPlayer(depth=4, enhance=True)\n",
    "alphabeta_minmax_player.train(n_games=20)\n",
    "alphabeta_minmax_player.save('trained_agents/alphabeta_minmax_depth4_player')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View Games"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- BEGINNING OF THE GAME --\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "Player ❌ chose to move (0, 1) to the top\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "Player ⭕️ chose to move (2, 4) to the right\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⭕️\n",
      "Player ❌ chose to move (0, 1) to the bottom\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⭕️\n",
      "Player ⭕️ chose to move (0, 1) to the top\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⭕️\n",
      "Player ❌ chose to move (4, 0) to the left\n",
      "❌⭕️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⭕️\n",
      "Player ⭕️ chose to move (3, 0) to the right\n",
      "❌⭕️⬜️⬜️⭕️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⭕️\n",
      "Player ❌ chose to move (0, 2) to the top\n",
      "❌⭕️⬜️⬜️⭕️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⭕️\n",
      "Player ⭕️ chose to move (0, 3) to the bottom\n",
      "❌⭕️⬜️⬜️⭕️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⭕️\n",
      "Player ❌ chose to move (2, 4) to the left\n",
      "❌⭕️⬜️⬜️⭕️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "❌⭕️⬜️⬜️⭕️\n",
      "Winner: Player 0\n",
      "-- END OF THE GAME --\n"
     ]
    }
   ],
   "source": [
    "# create the first player\n",
    "player1 = MinMaxPlayer()\n",
    "# create the second player\n",
    "player2 = RandomPlayer()\n",
    "# create a new game\n",
    "game = InvestigateGame(Game())\n",
    "# LET'S BATTLE\n",
    "winner = game.play(player1, player2, max_steps_draw=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Play Games"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- BEGINNING OF THE GAME --\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "Player ❌ chose to move (0, 1) to the top\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "Player ⭕️ chose to move (0, 1) to the bottom\n",
      "❌⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ❌ chose to move (4, 3) to the top\n",
      "❌⬜️⬜️⬜️❌\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ⭕️ chose to move (0, 1) to the bottom\n",
      "❌⬜️⬜️⬜️❌\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ❌ chose to move (2, 4) to the top\n",
      "❌⬜️❌⬜️❌\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ⭕️ chose to move (0, 1) to the bottom\n",
      "❌⬜️❌⬜️❌\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ❌ chose to move (3, 4) to the top\n",
      "❌⬜️❌❌❌\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ⭕️ chose to move (1, 0) to the left\n",
      "⭕️❌❌❌❌\n",
      "⬜️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Player ❌ chose to move (0, 1) to the top\n",
      "❌❌❌❌❌\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "⭕️⬜️⬜️⬜️⬜️\n",
      "Winner: Player 0\n",
      "-- END OF THE GAME --\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create the human player\n",
    "human_player = HumanPlayer()\n",
    "\n",
    "# create a mtcs player\n",
    "monte_carlo_tree_search = MCTSPlayer(n_simulations=500, random=True)\n",
    "\n",
    "# start the game\n",
    "g = InvestigateGame(Game())\n",
    "g.play(monte_carlo_rl_player, monte_carlo_tree_search, max_steps_draw=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing Players performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_game_statistics(player1: Player, player2: Player, n_games: int) -> None:\n",
    "    \"\"\"\n",
    "    Play a few games between two players and plot the calculated winning percentages.\n",
    "\n",
    "    Args:\n",
    "        players1: the first player;\n",
    "        players2: the second player;\n",
    "        n_games: how many games to play.\n",
    "\n",
    "    Returns:\n",
    "        None.\n",
    "    \"\"\"\n",
    "\n",
    "    # define the width and height of the figure in inches\n",
    "    plt.figure(figsize=(8, 5))\n",
    "\n",
    "    # let the players play both first and second\n",
    "    for plot, (player1, player2) in enumerate([(player1, player2), (player2, player1)]):\n",
    "        # count how many wins for the first player\n",
    "        player1_wins = 0\n",
    "\n",
    "        # for each game\n",
    "        for _ in range(n_games):\n",
    "            # create the game\n",
    "            game = Game()\n",
    "            # play the game\n",
    "            winner = game.play(player1, player2)\n",
    "            # if the first player wins\n",
    "            if winner == 0:\n",
    "                # increment the counter\n",
    "                player1_wins += 1\n",
    "\n",
    "        # create a subplot\n",
    "        plt.subplot(1, 2, plot + 1)\n",
    "        # plot the first player wins\n",
    "        bars = plt.bar([0, 0.6], [player1_wins, n_games - player1_wins], color=['royalblue', 'lightcoral'], width=0.4)\n",
    "        # for each bar\n",
    "        for bar in bars:\n",
    "            # get the winning percentage\n",
    "            percentage = bar.get_height() / n_games\n",
    "            # write the percentage on top of the bar\n",
    "            plt.text(\n",
    "                bar.get_x() + bar.get_width() / 2,\n",
    "                bar.get_height(),\n",
    "                f'{percentage:.2%}',\n",
    "                ha='center',\n",
    "                va='bottom',\n",
    "                fontsize='medium',\n",
    "            )\n",
    "        # plot the players' names\n",
    "        plt.xticks([0, 0.6], [player1.__class__.__name__, player2.__class__.__name__])\n",
    "        # delete y-axis ticks and labels\n",
    "        plt.tick_params(left=False, labelleft=False)\n",
    "        # specify the y-axis label\n",
    "        plt.ylabel('Wins')\n",
    "        # specify the title shared between the subplots\n",
    "        plt.title(\n",
    "            f'{player1.__class__.__name__.replace(\"Player\",\"\")} VS {player2.__class__.__name__.replace(\"Player\",\"\")}',\n",
    "            fontsize=10,\n",
    "        )\n",
    "\n",
    "    # specify the title shared between the subplots\n",
    "    plt.suptitle(f'Summary of {n_games} games')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_game_statistics(RandomPlayer(), MCTSPlayer(n_simulations=500, random=True), 100)\n",
    "show_game_statistics(RandomPlayer(), monte_carlo_rl_player, 100)\n",
    "show_game_statistics(RandomPlayer(), MinMaxPlayer(depth=3, enhance=True), 100)\n",
    "show_game_statistics(RandomPlayer(), AlphaBetaMinMaxPlayer(depth=3, enhance=True), 100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing MinMax implementations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def show_minmax_statistics(player: MinMaxPlayer, minute: bool = False) -> None:\n",
    "    \"\"\"\n",
    "    Play two games between the minmax player and a player that play randomly, and plot the duration time\n",
    "    of the game with different optimizations.\n",
    "\n",
    "    Args:\n",
    "        player: a minmax player to test.\n",
    "\n",
    "    Returns:\n",
    "        None.\n",
    "    \"\"\"\n",
    "\n",
    "    # define the width and height of the figure in inches\n",
    "    plt.figure(figsize=(8, 5))\n",
    "\n",
    "    # list to collect the duration time\n",
    "    data = []\n",
    "\n",
    "    # for each optimization\n",
    "    for label, (flag1, flag2) in {\n",
    "        'Hash table': (False, False),\n",
    "        'Parallization': (True, False),\n",
    "        'Symmetries': (False, True),\n",
    "        'Parallization\\n&\\nSymmetries': (True, True),\n",
    "        'Nothing': (False, False),\n",
    "    }.items():\n",
    "        # set the flags\n",
    "        player.parallelize(flag1)\n",
    "        player._symmetries = flag2\n",
    "        # create the game\n",
    "        game = Game()\n",
    "        # keep track of the start time\n",
    "        start = time.time()\n",
    "        # play the game\n",
    "        game.play(player, RandomPlayer())\n",
    "        # create the game\n",
    "        game = Game()\n",
    "        # play the game\n",
    "        game.play(RandomPlayer(), player)\n",
    "        # get the total time of a match\n",
    "        total_time = (time.time() - start) / 2\n",
    "        # append the data to plot\n",
    "        data.append((label, total_time))\n",
    "\n",
    "    # split labels and values\n",
    "    labels, values = zip(*sorted(data, key=lambda x: x[1]))\n",
    "    # plot the results\n",
    "    bars = plt.bar(labels, values, color=['deepskyblue'], width=0.5)\n",
    "    # for each bar\n",
    "    for i, bar in enumerate(bars):\n",
    "        # write the game duration on top of the bar\n",
    "        plt.text(\n",
    "            bar.get_x() + bar.get_width() / 2,\n",
    "            bar.get_height(),\n",
    "            (datetime.strftime(datetime.utcfromtimestamp(values[i]), \"%Mm %Ss %f\")[:-3] + \"ms\")\n",
    "            .replace('00m ', '')\n",
    "            .replace('00s ', '')\n",
    "            .replace(' 000ms', ''),\n",
    "            ha='center',\n",
    "            va='bottom',\n",
    "            fontsize='medium',\n",
    "        )\n",
    "\n",
    "    # delete y-axis ticks and labels\n",
    "    plt.tick_params(left=False, labelleft=False)\n",
    "    # specify the y-axis label\n",
    "    plt.ylabel('Time')\n",
    "    # specify the title\n",
    "    plt.title(f'How long does a game last?')\n",
    "    # add margins to the plot\n",
    "    plt.margins(y=0.2)\n",
    "    # add information text\n",
    "    plt.text(\n",
    "        -0.35,\n",
    "        values[-1] * (1.16),\n",
    "        f'{player.__class__.__name__} at depth {player._depth} VS RandomPlayer',\n",
    "        color=\"white\",\n",
    "        bbox=dict(facecolor='steelblue', boxstyle='round,pad=0.3,rounding_size=0.2'),\n",
    "        ha='left',\n",
    "        va='top',\n",
    "    )\n",
    "    # show the plot\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minmax_player = MinMaxPlayer()\n",
    "minmax_player.load('trained_agents/minmax_depth3_player.pkl')\n",
    "alphabeta_minmax_player = AlphaBetaMinMaxPlayer()\n",
    "alphabeta_minmax_player.load('trained_agents/alphabeta_minmax_depth4_player.pkl')\n",
    "show_minmax_statistics(minmax_player)\n",
    "show_minmax_statistics(alphabeta_minmax_player)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As can be seen from the results, parallelization of the first level of the MinMax search tree leads to the best results. Against our expectations, however, symmetries do not produce time improvements, but worsen the overall performance of the players."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ci",
   "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}