{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lawn Mower"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## n-step Bootstrapping \n",
    "\n",
    "Implement n-step Bootstrapping (e.g. n-step SARSA). Modify a base algorithm and implement 2-step or 3-step bootstrapping. Compare the results with base algorithm (e.g. SARSA, if you implemented n-step SARSA). In the report, include the comparison."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Episode: 100\n",
      "Q-table:\n",
      "[[ 3.94445164 10.08639766 18.91875449  8.69964422]\n",
      " [ 7.34899418  3.71372302 17.09500365  7.93464015]\n",
      " [11.32974305  4.85874467 19.55035796  6.03239534]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-5.53433024  8.20183027  1.51922077  0.27462116]\n",
      " [ 1.04285868  2.8370333   6.35619062 -2.30078456]\n",
      " [14.16538219 -0.0261558   3.4989501   0.04973516]\n",
      " [ 7.22021349  1.72988481  4.33230443  0.1380079 ]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091  5.96257258 -5.56560277]\n",
      " [ 0.14155166  1.81847876 14.82827911 -0.9072015 ]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -2.67309    -0.12012034]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.39\n",
      "Episode: 100, Average Steps: 9.8\n",
      "Episode: 200\n",
      "Q-table:\n",
      "[[24.07049497 29.58853666 34.63958723 26.67794259]\n",
      " [13.65531054 22.59559552 35.58492955 20.84896995]\n",
      " [23.71612368 24.77839724 38.44609845 18.56533933]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.32379693 21.57451859  5.46024258  7.58805976]\n",
      " [ 3.38484905  9.44147993 18.54356677  5.34398221]\n",
      " [13.27552685  4.47803229 17.28489036  0.04973516]\n",
      " [24.78174563 17.53989742  7.56554613  5.01902378]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 12.2470969  -5.56560277]\n",
      " [-0.63202067  8.79802815 16.20051301  2.97379367]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -0.12012034]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 0.          0.          0.         -1.79694   ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.12\n",
      "Episode: 200, Average Steps: 9.85\n",
      "Episode: 300\n",
      "Q-table:\n",
      "[[ 3.88708985e+01  4.30739636e+01  4.65073007e+01  3.50363694e+01]\n",
      " [ 1.98292639e+01  3.74985746e+01  4.59307229e+01  3.72224771e+01]\n",
      " [ 2.96317397e+01  3.16947444e+01  5.02489545e+01  3.09384305e+01]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00]\n",
      " [-1.03677532e+00  2.86498624e+01  1.08151091e+01  1.24440383e+01]\n",
      " [ 3.38484905e+00  9.44147993e+00  2.58076110e+01  5.34398221e+00]\n",
      " [ 1.81715584e+01  4.47803229e+00  2.70274681e+01  4.97351632e-02]\n",
      " [ 3.79784491e+01  2.15048002e+01  6.41422921e+00  1.47009679e+01]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00]\n",
      " [-1.72725121e+00 -4.06310911e-01  2.08411042e+01 -5.56560277e+00]\n",
      " [-6.32020666e-01  8.79802815e+00  2.42426292e+01  1.47734253e+01]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00]\n",
      " [-2.85254799e+00 -1.61959145e+00 -1.71682650e+00 -1.24898969e+00]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00 -1.79694000e+00]\n",
      " [ 0.00000000e+00  0.00000000e+00  0.00000000e+00  0.00000000e+00]]\n",
      "Average Penalties in Last 100 Episodes: 0.05\n",
      "Episode: 300, Average Steps: 9.86\n",
      "Episode: 400\n",
      "Q-table:\n",
      "[[34.60225315 38.38998347 44.01041727 25.8797345 ]\n",
      " [31.16731445 50.68706284 57.29499275 45.39396677]\n",
      " [25.34570243 46.93733011 59.47265833 43.10074613]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 31.79530076 10.81510914 12.44403827]\n",
      " [ 6.73774411  9.44147993 33.77956463 11.48853067]\n",
      " [18.17155836 10.48581347 26.32035618  5.9601476 ]\n",
      " [38.28421917 21.50480017  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 18.30078233 -5.56560277]\n",
      " [ 5.0693274  12.29077743 24.24262917 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.03\n",
      "Episode: 400, Average Steps: 9.93\n",
      "Episode: 500\n",
      "Q-table:\n",
      "[[41.68236118 51.63127723 55.84387676 50.55109704]\n",
      " [35.57342804 50.47027116 62.61486613 48.93997013]\n",
      " [32.20213862 46.31748941 65.81293805 48.0398428 ]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 51.52205704 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 46.66081725 11.48853067]\n",
      " [23.71808427 10.48581347 44.1443853   5.9601476 ]\n",
      " [45.30370742 28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.0\n",
      "Episode: 500, Average Steps: 9.96\n",
      "Episode: 600\n",
      "Q-table:\n",
      "[[51.88526811 54.92845285 58.84708791 40.81006726]\n",
      " [35.57342804 54.74826088 65.38422242 56.65596674]\n",
      " [37.47397966 46.31748941 73.18389269 50.11539022]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 57.33242728 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 46.66081725 11.48853067]\n",
      " [23.71808427 10.48581347 48.36738935  5.9601476 ]\n",
      " [46.59871695 28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.0\n",
      "Episode: 600, Average Steps: 10.0\n",
      "Episode: 700\n",
      "Q-table:\n",
      "[[46.50464968 54.27164687 63.5412253  48.19331652]\n",
      " [38.1279308  57.64970412 70.33167308 56.65596674]\n",
      " [37.47397966 49.87683786 74.04115561 50.11539022]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 46.01300431 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 49.54091023 11.48853067]\n",
      " [23.71808427 10.48581347 51.73399651  5.9601476 ]\n",
      " [58.20057105 28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.0\n",
      "Episode: 700, Average Steps: 10.0\n",
      "Episode: 800\n",
      "Q-table:\n",
      "[[53.94593005 52.90438439 62.32762607 48.22880781]\n",
      " [38.1279308  59.18458017 71.34299394 56.65596674]\n",
      " [37.47397966 49.87683786 75.34762983 50.11539022]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 42.94102633 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 49.54091023 11.48853067]\n",
      " [23.71808427 10.48581347 51.73399651  5.9601476 ]\n",
      " [46.99512908 28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.0\n",
      "Episode: 800, Average Steps: 10.0\n",
      "Episode: 900\n",
      "Q-table:\n",
      "[[39.75508029 48.9815546  63.95163655 51.05953514]\n",
      " [38.1279308  59.18458017 73.40910689 56.65596674]\n",
      " [41.80258909 56.11509851 77.41850245 50.11539022]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 49.62734564 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 49.54091023 11.48853067]\n",
      " [23.71808427 10.48581347 54.66610341  5.9601476 ]\n",
      " [51.3880661  28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.0\n",
      "Episode: 900, Average Steps: 10.0\n",
      "Episode: 1000\n",
      "Q-table:\n",
      "[[44.1256007  53.35813686 62.53869369 57.73107874]\n",
      " [38.1279308  59.18458017 71.41530477 56.65596674]\n",
      " [41.80258909 56.11509851 75.430626   52.7098201 ]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 49.62734564 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 49.54091023 11.48853067]\n",
      " [23.71808427 10.48581347 54.66610341  5.9601476 ]\n",
      " [54.92863864 28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n",
      "Average Penalties in Last 100 Episodes: 0.0\n",
      "Episode: 1000, Average Steps: 10.0\n"
     ]
    }
   ],
   "source": [
    "env = MyLawn()\n",
    "\n",
    "epsilon = 1.0  \n",
    "epsilon_min = 0.01\n",
    "gamma = 0.99 \n",
    "alpha = 0.15 \n",
    "decay_rate = 0.995  \n",
    "total_episodes = 1000 \n",
    "max_timestamp = 20\n",
    "qt = np.zeros((env.obs_space.n, env.action_space.n))\n",
    "\n",
    "rewards_epi = []\n",
    "epsilon_values = []\n",
    "steps_per_episode = []\n",
    "penalties_per_episode = []\n",
    "\n",
    "final_state = None\n",
    "\n",
    "# n-step parameter\n",
    "n_steps = 3\n",
    "\n",
    "for episode in range(total_episodes):\n",
    "    state, _ = env.reset()\n",
    "    state_index = env.obs_space_to_index(state)\n",
    "    total_rewards = 0\n",
    "    total_steps = 0\n",
    "    episode_buffer = []\n",
    "\n",
    "    action = env.action_space.sample() if np.random.uniform(0, 1) < epsilon else np.argmax(qt[state_index])\n",
    "\n",
    "    while True:\n",
    "        next_state, reward, terminated, truncated, _ = env.step(action)\n",
    "        total_steps += 1\n",
    "        next_strt_idx = env.obs_space_to_index(next_state)\n",
    "        next_action = env.action_space.sample() if np.random.uniform(0, 1) < epsilon else np.argmax(qt[next_strt_idx])\n",
    "        episode_buffer.append((state_index, action, reward))\n",
    "\n",
    "        if len(episode_buffer) >= n_steps:\n",
    "            n_step_return = sum([gamma ** i * ep[2] for i, ep in enumerate(episode_buffer[:n_steps])])\n",
    "            if not terminated and not truncated:\n",
    "                n_step_return += gamma ** n_steps * qt[next_strt_idx, next_action]\n",
    "\n",
    "            first_state, first_action, _ = episode_buffer.pop(0)\n",
    "            qt[first_state, first_action] = qt[first_state, first_action] + alpha * (n_step_return - qt[first_state, first_action])\n",
    "\n",
    "        state_index, action = next_strt_idx, next_action\n",
    "        total_rewards += reward\n",
    "\n",
    "        if terminated or truncated:\n",
    "            break\n",
    "\n",
    "    penalties_per_episode.append(env.get_penalty_count())\n",
    "\n",
    "    # Q-table for every 100 episodes\n",
    "    if (episode + 1) % 100 == 0:\n",
    "        print(f\"Episode: {episode + 1}\")\n",
    "        print(\"Q-table:\")\n",
    "        print(qt)\n",
    "\n",
    "        # average penalties\n",
    "        avg_penalty = np.mean(penalties_per_episode[-100:])\n",
    "        print(f\"Average Penalties in Last 100 Episodes: {avg_penalty}\")\n",
    "\n",
    "    epsilon = max(epsilon_min, epsilon * decay_rate)\n",
    "    epsilon_values.append(epsilon)\n",
    "    rewards_epi.append(total_rewards)\n",
    "    steps_per_episode.append(total_steps)\n",
    "\n",
    "    if (episode + 1) % 100 == 0:\n",
    "        average_steps = np.mean(steps_per_episode[-100:])\n",
    "        print(f\"Episode: {episode + 1}, Average Steps: {average_steps}\")\n",
    "\n",
    "    if episode == total_episodes - 1:\n",
    "        final_state = env.state\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "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(rewards_epi)\n",
    "plt.title('Total Reward per Episode')\n",
    "plt.xlabel('Episode')\n",
    "plt.ylabel('Total Reward')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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KlVNqaqo+/vjj63qOrirqjKfC6s8f9/+ls8KsgiCDUlWrVi199913ys7OdvpPd+fOnY7l+Yr6z2fevHlKTEzUq6++6mg7f/58gbMSroe3t7dSUlJ055136s0339To0aNVu3ZtSX+cweDKnoK2bdtq1apVio6O1q233qrg4GDdcsstCg0N1TfffKP09HSnM0i2bt2qn3/+We+//77+/ve/O9qXLl3qct21atVSXl6efvnlF6f/SvMPcbkqf49LPmOM9uzZ4/igzd/7EBIS4tJYlKTLa5Wkn3/+WeXLl1dkZOQVH3v77bfr9ttv1/jx4/Xxxx8rISFBc+bM0cMPP+zya9XVMc8/oyk3N/eaxszHx0d16tTRvn373H7sn/Xo0UP/93//5zi89PPPP2vMmDFOfebNm6c777xT7777rlP76dOnr/pBHh4eXuihmcv3hsyfP1/+/v5asmSJ057PPx8Ky+fqXpD838muXbscf6+SdOHCBe3bt++6Xqv79u2Tl5eX6tevf83rQMlgjgxKVdeuXZWbm+s4zTPfa6+9JpvN5nSmQGBgYKHhxNvbu8B/TG+88UaR8yGuVYcOHdSiRQtNmTJF58+fV6VKldShQwfNmDFDR44cKdD/+PHjTvfbtm2r/fv369NPP3UcavLy8lLr1q01efJkXbx40Wl+TP5/h39+bsYYTZ061eWa88fvz6d+S9KUKVNcXof0x4UMs7OzHffnzZunI0eOONYfGxurOnXqaNKkSTpz5kyBx18+FiVp7dq1TnMqMjIy9OWXX6pTp05F/sd96tSpAq+h/D1L+Yc4XH2tujrm3t7e6tWrl+bPn1/o5e5dGbNWrVrpp59+umq/KwkLC1N8fLw+++wzzZkzR76+vgUuNFfY39jcuXNdutJ1nTp1tHPnTqfns2XLlgKn5Xt7e8tmszn93e7fv7/QK/gW9V5wubi4OPn6+ur11193qv/dd99VVlaW22fv/dnGjRvVuHFjhYaGXvM6UDLYI4NSde+99+rOO+/UM888o/379+uWW27Rt99+qy+//FLDhg1zmmcQGxur7777TpMnT3YcqmnZsqXuueceffjhhwoNDVWjRo20du1afffdd8V67D7fU089pd69e2vWrFl69NFH9dZbb6lNmzZq0qSJBg0apNq1a+vo0aNau3atfv31V6frbOSHlF27dmnChAmO9nbt2mnx4sXy8/NzunJtw4YNVadOHY0cOVKHDh1SSEiI5s+f79ahhFtvvVUPPfSQpk2bpqysLLVu3Vrff/+99uzZ49bzrlChgtq0aaOkpCQdPXpUU6ZMUd26dTVo0CBJfwSyf/3rX+rSpYsaN26spKQkVa9eXYcOHdLy5csVEhKir776yq1tXm716tU6f/58gfamTZs6HYKJiYlRfHy80+nXkgq9Xkq+999/X9OmTVPPnj1Vp04dZWdna+bMmQoJCVHXrl0luf5adWfMJ06cqOXLl6tly5YaNGiQGjVqpJMnTyo9PV3fffddoadP/9l9992nDz/8UD///HOhewbmzZtX6GGxu+++W5UrV3bc/+tf/6p+/fpp2rRpio+PL3Dl33vuuUcvvviikpKS1Lp1a23dulWzZ8922stRlAEDBmjy5MmKj4/XwIEDdezYMb399ttq3Lix7Ha7o1+3bt00efJkde7cWX379tWxY8f01ltvqW7dugXmqBT1XnC5yMhIjRkzRmPHjlXnzp3VvXt37dq1S9OmTdNf/vKXa74w58WLF7Vy5Uo99thj1/R4lLBSPUcK/3MuP/3aGGOys7PN8OHDTbVq1Uy5cuVMvXr1zCuvvOJ0Gq8xxuzcudO0a9fOBAQEGEmO0y9PnTplkpKSTMWKFU1QUJCJj483O3fuNLVq1XI6RdPd068LOxU3NzfX1KlTx9SpU8dcunTJGGPML7/8Yv7+97+bKlWqmHLlypnq1aube+65x8ybN6/A4ytVqmQkmaNHjzra1qxZYySZtm3bFui/fft2ExcXZ4KCgkzFihXNoEGDzJYtWwqc4pqYmGgCAwMLfT6///67GTJkiImIiDCBgYHm3nvvNRkZGW6dfv3JJ5+YMWPGmEqVKpmAgADTrVs3p9O/823atMncf//9JiIiwvj5+ZlatWqZBx980Hz//feOPvmnBh8/fvyK2768hqJuf34OkkxycrL56KOPTL169Yyfn59p1qxZgd/55afppqenm4ceesjUrFnT+Pn5mUqVKpl77rnH6TRuY1x/rboz5kePHjXJyckmKirKlCtXzlSpUsV07NjRvPPOO1cdm5ycHFOxYkXz0ksvObVf6fTrwv4G7Ha74+/qo48+KrCd8+fPmyeffNJUrVrVBAQEmDvuuMOsXbu2wKnVhZ1+bYwxH330kaldu7bx9fU1t956q1myZEmhp1+/++67jt9bw4YNTWpqquO5/FlR7wWX/17zvfnmm6Zhw4amXLlypnLlymbw4MHm1KlTTn3at29vGjduXOC5F1bn4sWLjSSze/fuAv3heTZjXLgyFYD/CStWrNCdd96puXPnFtvXA5Qkm82m5OTkAod/bmQvvfSSUlNTtXv37hviaxesoEePHrLZbPriiy88XQoKwRwZALCQ4cOH68yZM//z3wJeWnbs2KFFixY5TldH2cMcGQCwkKCgIJeuN4PicfPNN+vSpUueLgNXwB4ZAABgWcyRAQAAlsUeGQAAYFkEGQAAYFk3/GTfvLw8HT58WMHBwXzZFwAAFmGMUXZ2tqpVq3bF75W74YPM4cOHFRUV5ekyAADANcjIyFCNGjWKXH7DB5n8L3vLyMhQSEiIh6sBAACusNvtioqKcvrS1sLc8EEm/3BSSEgIQQYAAIu52rQQJvsCAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLIsgAAADLKjNBZuLEibLZbBo2bFiBZcYYdenSRTabTQsWLCj12gAAQNlUJoJMWlqaZsyYoaZNmxa6fMqUKbLZbKVcFQAAKOs8HmTOnDmjhIQEzZw5U+Hh4QWWb968Wa+++qree+89D1QHAADKMo8HmeTkZHXr1k1xcXEFlp07d059+/bVW2+9pSpVqri0vpycHNntdqcbAAC4Mfl4cuNz5sxRenq60tLSCl0+fPhwtW7dWvfdd5/L60xJSdHYsWOLq0QAAFCGeSzIZGRkaOjQoVq6dKn8/f0LLF+4cKGWLVumTZs2ubXeMWPGaMSIEY77drtdUVFR110vAAAoe2zGGOOJDS9YsEA9e/aUt7e3oy03N1c2m01eXl4aPHiw3nrrLXl5eTkt9/LyUtu2bbVixQqXtmO32xUaGqqsrCyFhIQU99MAAAAlwNXPb48FmezsbB04cMCpLSkpSQ0bNtSoUaNUsWJFnThxwml5kyZNNHXqVN17772Kjo52aTsEGQAArMfVz2+PHVoKDg5WTEyMU1tgYKAiIiIc7YVN8K1Zs6bLIQYAANzYPH7WEgAAwLXy6FlLl7vavBcPHQUDAABlFHtkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZRFkAACAZZWZIDNx4kTZbDYNGzbM0fZ///d/qlOnjgICAhQZGan77rtPO3fu9FyRAACgTCkTQSYtLU0zZsxQ06ZNndpjY2OVmpqqHTt2aMmSJTLGqFOnTsrNzfVQpQAAoCzxeJA5c+aMEhISNHPmTIWHhzste+SRR9SuXTvddNNNuu222zRu3DhlZGRo//79nikWAACUKR4PMsnJyerWrZvi4uKu2O/s2bNKTU1VdHS0oqKiiuyXk5Mju93udAMAADcmjwaZOXPmKD09XSkpKUX2mTZtmoKCghQUFKTFixdr6dKl8vX1LbJ/SkqKQkNDHbcrhR4AAGBtHgsyGRkZGjp0qGbPni1/f/8i+yUkJGjTpk1auXKl6tevrwcffFDnz58vsv+YMWOUlZXluGVkZJRE+QAAoAywGWOMJza8YMEC9ezZU97e3o623Nxc2Ww2eXl5KScnx2mZJF24cEHh4eH617/+pYceesil7djtdoWGhiorK0shISHF+hwAAEDJcPXz26cUa3LSsWNHbd261aktKSlJDRs21KhRowqEGEkyxsgYo5ycnNIqEwAAlGEeCzLBwcGKiYlxagsMDFRERIRiYmK0d+9effrpp+rUqZMiIyP166+/auLEiQoICFDXrl09VDUAAChLPH7WUlH8/f21evVqde3aVXXr1tVf//pXBQcH68cff1SlSpU8XR4AACgDPDZHprQwRwYAAOtx9fO7zO6RAQAAuBqCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCyCDAAAsCwfVzqNGDHC5RVOnjz5mosBAABwh0tBZtOmTU7309PTdenSJTVo0ECS9PPPP8vb21uxsbHFXyEAAEARXAoyy5cvd/w8efJkBQcH6/3331d4eLgk6dSpU0pKSlLbtm1LpkoAAIBC2Iwxxp0HVK9eXd9++60aN27s1L5t2zZ16tRJhw8fLtYCr5fdbldoaKiysrIUEhLi6XIAAIALXP38dnuyr91u1/Hjxwu0Hz9+XNnZ2e6uDgAA4Jq5HWR69uyppKQkff755/r111/166+/av78+Ro4cKDuv//+kqgRAACgUC7Nkfmzt99+WyNHjlTfvn118eLFP1bi46OBAwfqlVdeKfYCAQAAiuLWHJnc3Fz98MMPatKkiXx9ffXLL79IkurUqaPAwMASK/J6MEcGAADrcfXz2609Mt7e3urUqZN27Nih6OhoNW3a9LoLBQAAuFZuz5GJiYnR3r17S6IWAAAAt7gdZMaNG6eRI0dq0aJFOnLkiOx2u9MNAACgtLh9HRkvr/+ffWw2m+NnY4xsNptyc3OLr7piwBwZAACsp0TmyEjOV/kFAADwJLeDTPv27UuiDgAAALe5HWTynTt3TgcPHtSFCxec2jmTCQAAlBa3g8zx48eVlJSkxYsXF7q8rM2RAQAANy63z1oaNmyYTp8+rfXr1ysgIEDffPON3n//fdWrV08LFy4siRoBAAAK5fYemWXLlunLL79U8+bN5eXlpVq1aunuu+9WSEiIUlJS1K1bt5KoEwAAoAC398icPXtWlSpVkiSFh4c7vgm7SZMmSk9PL97qAAAArsDtINOgQQPt2rVLknTLLbdoxowZOnTokN5++21VrVq12AsEAAAoituHloYOHaojR45Ikp5//nl17txZs2fPlq+vr2bNmlXc9QEAABTJ7Sv7Xu7cuXPauXOnatasqYoVKxZXXcWGK/sCAGA9rn5+u31o6fIvjCxfvrxuu+22MhliAADAjc3tQ0t169ZVjRo11L59e3Xo0EHt27dX3bp1S6I2AACAK3J7j0xGRoZSUlIUEBCgl19+WfXr11eNGjWUkJCgf/3rXyVRIwAAQKGue47M7t27NX78eM2ePVt5eXll7sq+zJEBAMB6Suzbr8+dO6c1a9ZoxYoVWrFihTZt2qSGDRvq8ccfV4cOHa6nZgAAALe4HWTCwsIUHh6uhIQEjR49Wm3btlV4eHhJ1AYAAHBFbgeZrl27as2aNZozZ44yMzOVmZmpDh06qH79+iVRHwAAQJHcnuy7YMECnThxQt98841atWqlb7/9Vm3btlX16tWVkJBQEjUCAAAUyu09MvmaNGmiS5cu6cKFCzp//ryWLFmiTz/9VLNnzy7O+gAAAIrk9h6ZyZMnq3v37oqIiFDLli31ySefqH79+po/f77jCyQBAABKg9t7ZD755BO1b99ejzzyiNq2bavQ0NCSqAsAAOCq3A4yaWlpJVEHAACA29w+tCRJq1evVr9+/dSqVSsdOnRIkvThhx9qzZo1xVocAADAlbgdZObPn6/4+HgFBARo06ZNysnJkSRlZWVpwoQJxV4gAABAUdwOMuPGjdPbb7+tmTNnqly5co72O+64Q+np6cVaHAAAwJW4HWR27dqldu3aFWgPDQ3V6dOni6MmAAAAl7gdZKpUqaI9e/YUaF+zZo1q1659zYVMnDhRNptNw4YNkySdPHlSTzzxhBo0aKCAgADVrFlTQ4YMUVZW1jVvAwAA3FjcDjKDBg3S0KFDtX79etlsNh0+fFizZ8/WyJEjNXjw4GsqIi0tTTNmzFDTpk0dbYcPH9bhw4c1adIkbdu2TbNmzdI333yjgQMHXtM2AADAjcft069Hjx6tvLw8dezYUefOnVO7du3k5+enkSNH6oknnnC7gDNnzighIUEzZ87UuHHjHO0xMTGaP3++436dOnU0fvx49evXT5cuXZKPzzVflPi6GWP0+8Vcj20fAICyJKCct2w2m0e27XYasNlseuaZZ/TUU09pz549OnPmjBo1aqSgoCD9/vvvCggIcGt9ycnJ6tatm+Li4pyCTGGysrIUEhJyxRCTk5PjOJNKkux2u1v1uOL3i7lq9NySYl8vAABWtP3FeJX39cwOhmu6jowk+fr6qlGjRmrRooXKlSunyZMnKzo62q11zJkzR+np6UpJSblq3xMnTuill17SI488csV+KSkpCg0NddyioqLcqgkAAFiHy/EpJydHL7zwgpYuXSpfX1/94x//UI8ePZSamqpnnnlG3t7eGj58uMsbzsjI0NChQ7V06VL5+/tfsa/dble3bt3UqFEjvfDCC1fsO2bMGI0YMcLpscUdZgLKeWv7i/HFuk4AAKwqoJy3x7ZtM8YYVzqOGjVKM2bMUFxcnH788UcdP35cSUlJWrdunZ5++mn17t1b3t6uP5EFCxaoZ8+eTo/Jzc2VzWaTl5eXcnJy5O3trezsbMXHx6t8+fJatGjRVUPP5ex2u0JDQx2HpQAAQNnn6ue3y3tk5s6dqw8++EDdu3fXtm3b1LRpU126dElbtmy5pgk+HTt21NatW53akpKS1LBhQ40aNUre3t6y2+2Kj4+Xn5+fFi5c6HaIAQAANzaXg8yvv/6q2NhYSX+cUeTn56fhw4df8yzl4OBgxcTEOLUFBgYqIiJCMTExstvt6tSpk86dO6ePPvpIdrvdMXE3MjLSrb0/AADgxuRykMnNzZWvr+//f6CPj4KCgkqkKElKT0/X+vXrJUl169Z1WrZv3z7ddNNNJbZtAABgDS7PkfHy8lKXLl3k5+cnSfrqq6901113KTAw0Knf559/XvxVXgfmyAAAYD3FPkcmMTHR6X6/fv2uvToAAIBi4HKQSU1NLck6AAAA3HbNF8QDAADwNIIMAACwLIIMAACwLIIMAACwLIIMAACwLJfOWlq4cKHLK+zevfs1FwMAAOAOl4JMjx49XFqZzWZTbm7u9dQDAADgMpeCTF5eXknXAQAA4DbmyAAAAMty+cq+f3b27FmtXLlSBw8e1IULF5yWDRkypFgKAwAAuBq3g8ymTZvUtWtXnTt3TmfPnlWFChV04sQJlS9fXpUqVSLIAACAUuP2oaXhw4fr3nvv1alTpxQQEKB169bpwIEDio2N1aRJk0qiRgAAgEK5HWQ2b96sJ598Ul5eXvL29lZOTo6ioqL08ssv6+mnny6JGgEAAArldpApV66cvLz+eFilSpV08OBBSVJoaKgyMjKKtzoAAIArcHuOTLNmzZSWlqZ69eqpffv2eu6553TixAl9+OGHiomJKYkaAQAACuX2HpkJEyaoatWqkqTx48crPDxcgwcP1vHjxzVjxoxiLxAAAKAoNmOM8XQRJclutys0NFRZWVkKCQnxdDkAAMAFrn5+u71H5q677tLp06cL3eBdd93l7uoAAACumdtBZsWKFQUugidJ58+f1+rVq4ulKAAAAFe4PNn3P//5j+Pn7du3KzMz03E/NzdX33zzjapXr1681QEAAFyBy0Hm1ltvlc1mk81mK/QQUkBAgN54441iLQ4AAOBKXA4y+/btkzFGtWvX1oYNGxQZGelY5uvrq0qVKsnb27tEigQAACiMy0GmVq1akqS8vLwSKwYAAMAd1/Tt17/88oumTJmiHTt2SJIaNWqkoUOHqk6dOsVaHAAAwJW4fdbSkiVL1KhRI23YsEFNmzZV06ZNtX79ejVu3FhLly4tiRoBAAAK5fYF8Zo1a6b4+HhNnDjRqX306NH69ttvlZ6eXqwFXi8uiAcAgPWU2AXxduzYoYEDBxZoHzBggLZv3+7u6gAAAK6Z20EmMjJSmzdvLtC+efNmVapUqThqAgAAcInLk31ffPFFjRw5UoMGDdIjjzyivXv3qnXr1pKkH374Qf/85z81YsSIEisUAADgci7PkfH29taRI0cUGRmpKVOm6NVXX9Xhw4clSdWqVdNTTz2lIUOGyGazlWjB7mKODAAA1uPq57fLQcbLy0uZmZlOh4+ys7MlScHBwddZbskhyAAAYD2ufn67dR2Zy/e2lOUAAwAAbnxuBZn69etf9dDRyZMnr6sgAAAAV7kVZMaOHavQ0NCSqgUAAMAtbgWZPn36cIo1AAAoM1y+jkxZOxsJAADA5SDj5jcZAAAAlDiXDy3l5eWVZB0AAABuc/srCgAAAMoKggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALAsggwAALCsMhNkJk6cKJvNpmHDhjna3nnnHXXo0EEhISGy2Ww6ffq0x+oDAABlT5kIMmlpaZoxY4aaNm3q1H7u3Dl17txZTz/9tIcqAwAAZZmPpws4c+aMEhISNHPmTI0bN85pWf7emRUrVpR+YQAAoMzz+B6Z5ORkdevWTXFxccWyvpycHNntdqcbAAC4MXl0j8ycOXOUnp6utLS0YltnSkqKxo4dW2zrAwAAZZfH9shkZGRo6NChmj17tvz9/YttvWPGjFFWVpbjlpGRUWzrBgAAZYvH9shs3LhRx44d02233eZoy83N1apVq/Tmm28qJydH3t7ebq/Xz89Pfn5+xVkqAAAoozwWZDp27KitW7c6tSUlJalhw4YaNWrUNYUYAADwv8VjQSY4OFgxMTFObYGBgYqIiHC0Z2ZmKjMzU3v27JEkbd26VcHBwapZs6YqVKhQ6jUDAICyxeNnLV3J22+/rWbNmmnQoEGSpHbt2qlZs2ZauHChhysDAABlgc0YYzxdREmy2+0KDQ1VVlaWQkJCPF0OAABwgauf32V6jwwAAMCVEGQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBlEWQAAIBllZkgM3HiRNlsNg0bNszRdv78eSUnJysiIkJBQUHq1auXjh496rkiAQBAmVImgkxaWppmzJihpk2bOrUPHz5cX331lebOnauVK1fq8OHDuv/++z1UJQAAKGs8HmTOnDmjhIQEzZw5U+Hh4Y72rKwsvfvuu5o8ebLuuusuxcbGKjU1VT/++KPWrVvnwYoBAEBZ4fEgk5ycrG7duikuLs6pfePGjbp48aJTe8OGDVWzZk2tXbu2yPXl5OTIbrc73QAAwI3Jx5MbnzNnjtLT05WWllZgWWZmpnx9fRUWFubUXrlyZWVmZha5zpSUFI0dO7a4SwUAAGWQx/bIZGRkaOjQoZo9e7b8/f2Lbb1jxoxRVlaW45aRkVFs6wYAAGWLx4LMxo0bdezYMd12223y8fGRj4+PVq5cqddff10+Pj6qXLmyLly4oNOnTzs97ujRo6pSpUqR6/Xz81NISIjTDQAA3Jg8dmipY8eO2rp1q1NbUlKSGjZsqFGjRikqKkrlypXT999/r169ekmSdu3apYMHD6pVq1aeKBkAAJQxHgsywcHBiomJcWoLDAxURESEo33gwIEaMWKEKlSooJCQED3xxBNq1aqVbr/9dk+UDAAAyhiPTva9mtdee01eXl7q1auXcnJyFB8fr2nTpnm6LAAAUEbYjDHG00WUJLvdrtDQUGVlZTFfBgAAi3D189vj15EBAAC4VgQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWQQZAABgWT6eLqCkGWMkSXa73cOVAAAAV+V/bud/jhflhg8y2dnZkqSoqCgPVwIAANyVnZ2t0NDQIpfbzNWijsXl5eXp8OHDCg4Ols1mK7b12u12RUVFKSMjQyEhIcW2XhSO8S49jHXpYaxLD2NdeoprrI0xys7OVrVq1eTlVfRMmBt+j4yXl5dq1KhRYusPCQnhj6IUMd6lh7EuPYx16WGsS09xjPWV9sTkY7IvAACwLIIMAACwLILMNfLz89Pzzz8vPz8/T5fyP4HxLj2MdelhrEsPY116Snusb/jJvgAA4MbFHhkAAGBZBBkAAGBZBBkAAGBZBBkAAGBZBJlr9NZbb+mmm26Sv7+/WrZsqQ0bNni6JMtLSUnRX/7yFwUHB6tSpUrq0aOHdu3a5dTn/PnzSk5OVkREhIKCgtSrVy8dPXrUQxXfOCZOnCibzaZhw4Y52hjr4nPo0CH169dPERERCggIUJMmTfTTTz85lhtj9Nxzz6lq1aoKCAhQXFycdu/e7cGKrSk3N1fPPvusoqOjFRAQoDp16uill15y+q4exvrarFq1Svfee6+qVasmm82mBQsWOC13ZVxPnjyphIQEhYSEKCwsTAMHDtSZM2euvzgDt82ZM8f4+vqa9957z/z3v/81gwYNMmFhYebo0aOeLs3S4uPjTWpqqtm2bZvZvHmz6dq1q6lZs6Y5c+aMo8+jjz5qoqKizPfff29++uknc/vtt5vWrVt7sGrr27Bhg7nppptM06ZNzdChQx3tjHXxOHnypKlVq5bp37+/Wb9+vdm7d69ZsmSJ2bNnj6PPxIkTTWhoqFmwYIHZsmWL6d69u4mOjja///67Byu3nvHjx5uIiAizaNEis2/fPjN37lwTFBRkpk6d6ujDWF+br7/+2jzzzDPm888/N5LMF1984bTclXHt3LmzueWWW8y6devM6tWrTd26dc1DDz103bURZK5BixYtTHJysuN+bm6uqVatmklJSfFgVTeeY8eOGUlm5cqVxhhjTp8+bcqVK2fmzp3r6LNjxw4jyaxdu9ZTZVpadna2qVevnlm6dKlp3769I8gw1sVn1KhRpk2bNkUuz8vLM1WqVDGvvPKKo+306dPGz8/PfPLJJ6VR4g2jW7duZsCAAU5t999/v0lISDDGMNbF5fIg48q4bt++3UgyaWlpjj6LFy82NpvNHDp06Lrq4dCSmy5cuKCNGzcqLi7O0ebl5aW4uDitXbvWg5XdeLKysiRJFSpUkCRt3LhRFy9edBr7hg0bqmbNmoz9NUpOTla3bt2cxlRirIvTwoUL1bx5c/Xu3VuVKlVSs2bNNHPmTMfyffv2KTMz02msQ0ND1bJlS8baTa1bt9b333+vn3/+WZK0ZcsWrVmzRl26dJHEWJcUV8Z17dq1CgsLU/PmzR194uLi5OXlpfXr11/X9m/4L40sbidOnFBubq4qV67s1F65cmXt3LnTQ1XdePLy8jRs2DDdcccdiomJkSRlZmbK19dXYWFhTn0rV66szMxMD1RpbXPmzFF6errS0tIKLGOsi8/evXs1ffp0jRgxQk8//bTS0tI0ZMgQ+fr6KjEx0TGehb2nMNbuGT16tOx2uxo2bChvb2/l5uZq/PjxSkhIkCTGuoS4Mq6ZmZmqVKmS03IfHx9VqFDhuseeIIMyKTk5Wdu2bdOaNWs8XcoNKSMjQ0OHDtXSpUvl7+/v6XJuaHl5eWrevLkmTJggSWrWrJm2bdumt99+W4mJiR6u7sby2Wefafbs2fr444/VuHFjbd68WcOGDVO1atUY6xsYh5bcVLFiRXl7exc4e+Po0aOqUqWKh6q6sTz++ONatGiRli9frho1ajjaq1SpogsXLuj06dNO/Rl7923cuFHHjh3TbbfdJh8fH/n4+GjlypV6/fXX5ePjo8qVKzPWxaRq1apq1KiRU9vNN9+sgwcPSpJjPHlPuX5PPfWURo8erT59+qhJkyb629/+puHDhyslJUUSY11SXBnXKlWq6NixY07LL126pJMnT1732BNk3OTr66vY2Fh9//33jra8vDx9//33atWqlQcrsz5jjB5//HF98cUXWrZsmaKjo52Wx8bGqly5ck5jv2vXLh08eJCxd1PHjh21detWbd682XFr3ry5EhISHD8z1sXjjjvuKHAZgZ9//lm1atWSJEVHR6tKlSpOY22327V+/XrG2k3nzp2Tl5fzx5q3t7fy8vIkMdYlxZVxbdWqlU6fPq2NGzc6+ixbtkx5eXlq2bLl9RVwXVOF/0fNmTPH+Pn5mVmzZpnt27ebRx55xISFhZnMzExPl2ZpgwcPNqGhoWbFihXmyJEjjtu5c+ccfR599FFTs2ZNs2zZMvPTTz+ZVq1amVatWnmw6hvHn89aMoaxLi4bNmwwPj4+Zvz48Wb37t1m9uzZpnz58uajjz5y9Jk4caIJCwszX375pfnPf/5j7rvvPk4JvgaJiYmmevXqjtOvP//8c1OxYkXzj3/8w9GHsb422dnZZtOmTWbTpk1Gkpk8ebLZtGmTOXDggDHGtXHt3LmzadasmVm/fr1Zs2aNqVevHqdfe9Ibb7xhatasaXx9fU2LFi3MunXrPF2S5Ukq9Jaamuro8/vvv5vHHnvMhIeHm/Lly5uePXuaI0eOeK7oG8jlQYaxLj5fffWViYmJMX5+fqZhw4bmnXfecVqel5dnnn32WVO5cmXj5+dnOnbsaHbt2uWhaq3LbreboUOHmpo1axp/f39Tu3Zt88wzz5icnBxHH8b62ixfvrzQ9+fExERjjGvj+ttvv5mHHnrIBAUFmZCQEJOUlGSys7OvuzabMX+65CEAAICFMEcGAABYFkEGAABYFkEGAABYFkEGAABYFkEGAABYFkEGAABYFkEGAABYFkEGQJm0f/9+2Ww2bd68ucS20b9/f/Xo0aPE1g+g5BFkAJSI/v37y2azFbh17tzZpcdHRUXpyJEjiomJKeFKAViZj6cLAHDj6ty5s1JTU53a/Pz8XHqst7c330gM4KrYIwOgxPj5+alKlSpOt/DwcEmSzWbT9OnT1aVLFwUEBKh27dqaN2+e47GXH1o6deqUEhISFBkZqYCAANWrV88pJG3dulV33XWXAgICFBERoUceeURnzpxxLM/NzdWIESMUFhamiIgI/eMf/9Dl39CSl5enlJQURUdHKyAgQLfccotTTQDKHoIMAI959tln1atXL23ZskUJCQnq06ePduzYUWTf7du3a/HixdqxY4emT5+uihUrSpLOnj2r+Ph4hYeHKy0tTXPnztV3332nxx9/3PH4V199VbNmzdJ7772nNWvW6OTJk/riiy+ctpGSkqIPPvhAb7/9tv773/9q+PDh6tevn1auXFlygwDg+lz3104CQCESExONt7e3CQwMdLqNHz/eGPPHt50/+uijTo9p2bKlGTx4sDHGmH379hlJZtOmTcYYY+69916TlJRU6LbeeecdEx4ebs6cOeNo+/e//228vLxMZmamMcaYqlWrmpdfftmx/OLFi6ZGjRrmvvvuM8YYc/78eVO+fHnz448/Oq174MCB5qGHHrr2gQBQopgjA6DE3HnnnZo+fbpTW4UKFRw/t2rVymlZq1atijxLafDgwerVq5fS09PVqVMn9ejRQ61bt5Yk7dixQ7fccosCAwMd/e+44w7l5eVp165d8vf315EjR9SyZUvHch8fHzVv3txxeGnPnj06d+6c7r77bqftXrhwQc2aNXP/yQMoFQQZACUmMDBQdevWLZZ1denSRQcOHNDXX3+tpUuXqmPHjkpOTtakSZOKZf3582n+/e9/q3r16k7LXJ2gDKD0MUcGgMesW7euwP2bb765yP6RkZFKTEzURx99pClTpuidd96RJN18883asmWLzp496+j7ww8/yMvLSw0aNFBoaKiqVq2q9evXO5ZfunRJGzdudNxv1KiR/Pz8dPDgQdWtW9fpFhUVVVxPGUAxY48MgBKTk5OjzMxMpzYfHx/HJN25c+eqefPmatOmjWbPnq0NGzbo3XffLXRdzz33nGJjY9W4cWPl5ORo0aJFjtCTkJCg559/XomJiXrhhRd0/PhxPfHEE/rb3/6mypUrS5KGDh2qiRMnql69emrYsKEmT56s06dPO9YfHByskSNHavjw4crLy1ObNm2UlZWlH374QSEhIUpMTCyBEQJwvQgyAErMN998o6pVqzq1NWjQQDt37pQkjR07VnPmzNFjjz2mqlWr6pNPPlGjRo0KXZevr6/GjBmj/fv3KyAgQG3bttWcOXMkSeXLl9eSJUs0dOhQ/eUvf1H58uXVq1cvTZ482fH4J598UkeOHFFiYqK8vLw0YMAA9ezZU1lZWY4+L730kiIjI5WSkqK9e/cqLCxMt912m55++uniHhoAxcRmzGUXUgCAUmCz2fTFF1/wFQEArgtzZAAAgGURZAAAgGUxRwaAR3BUG0BxYI8MAACwLIIMAACwLIIMAACwLIIMAACwLIIMAACwLIIMAACwLIIMAACwLIIMAACwLIIMAACwrP8HJxVMbwmkJAIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Q-table:\n",
      "[[44.1256007  53.35813686 62.53869369 57.73107874]\n",
      " [38.1279308  59.18458017 71.41530477 56.65596674]\n",
      " [41.80258909 56.11509851 75.430626   52.7098201 ]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [ 3.76576835 49.62734564 10.81510914 12.44403827]\n",
      " [14.11605849  9.44147993 49.54091023 11.48853067]\n",
      " [23.71808427 10.48581347 54.66610341  5.9601476 ]\n",
      " [54.92863864 28.19988676  6.41422921 16.76306704]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-1.72725121 -0.40631091 20.89423826 -5.56560277]\n",
      " [ 5.0693274  12.29077743 40.95858916 19.16889889]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-2.85254799 -1.61959145 -1.7168265  -1.24898969]\n",
      " [ 0.          0.          0.          0.        ]\n",
      " [-0.9207015   0.          0.         -2.4569505 ]\n",
      " [ 0.          0.          0.          0.        ]]\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def evaluate_n_step_sarsa(env, q_table, n_steps):\n",
    "    total_episodes = 100\n",
    "    total_rewards_eval = []\n",
    "\n",
    "    for episode in range(total_episodes):\n",
    "        state, _ = env.reset()\n",
    "        state_index = env.obs_space_to_index(state)\n",
    "        total_rewards = 0\n",
    "\n",
    "        while True:\n",
    "            action = np.argmax(q_table[state_index])\n",
    "            next_state, reward, terminated, truncated, _ = env.step(action)\n",
    "            next_state_index = env.obs_space_to_index(next_state)\n",
    "            n_step_return = reward\n",
    "            for i in range(1, n_steps + 1):\n",
    "                if not terminated and not truncated:\n",
    "                    n_step_return += env.gamma ** i * q_table[next_state_index, np.argmax(q_table[next_state_index])]\n",
    "            \n",
    "            total_rewards += reward\n",
    "            state_index = next_state_index\n",
    "\n",
    "            if terminated or truncated:\n",
    "                break\n",
    "\n",
    "        total_rewards_eval.append(total_rewards)\n",
    "    return total_rewards_eval\n",
    "\n",
    "eval_rewards = evaluate_n_step_sarsa(env, qt, n_steps)\n",
    "\n",
    "plt.plot(eval_rewards)\n",
    "plt.title('Total Reward per Episode (Evaluation)')\n",
    "plt.xlabel('Episode')\n",
    "plt.ylabel('Total Reward')\n",
    "plt.show()\n",
    "\n",
    "print(\"Q-table:\")\n",
    "print(qt)\n",
    "\n",
    "plt.plot(epsilon_values)\n",
    "plt.title('Epsilon Decay during Training')\n",
    "plt.xlabel('Episode')\n",
    "plt.ylabel('Epsilon Value')\n",
    "plt.show()\n"
   ]
  }
 ],
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