3-body.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 69,
      "metadata": {
        "id": "9FfWo5DNacSn"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "\n",
        "def forward_euler_step(h, x, y, vx, vy, masses, eps = 1e-3):\n",
        "    G = 1  # Gravitational constant\n",
        "    \n",
        "    # add noise each step to see if the controller can figure out\n",
        "    x += eps * np.random.rand(3)\n",
        "    y += eps * np.random.rand(3)\n",
        "\n",
        "    # Compute center of mass and total momentum\n",
        "    cm = np.sum(x * masses) / np.sum(masses), np.sum(y * masses) / np.sum(masses)\n",
        "    p = np.sum(masses.reshape((3,1)) * np.vstack((vx, vy)).T, axis=0)\n",
        "    \n",
        "    # Subtract center of mass and total momentum\n",
        "    x -= cm[0]\n",
        "    y -= cm[1]\n",
        "    vx -= p[0] / np.sum(masses)\n",
        "    vy -= p[1] / np.sum(masses)\n",
        "\n",
        "    # Compute distances\n",
        "    r12 = np.sqrt((x[0] - x[1])**2 + (y[0] - y[1])**2)\n",
        "    r13 = np.sqrt((x[0] - x[2])**2 + (y[0] - y[2])**2)\n",
        "    r23 = np.sqrt((x[1] - x[2])**2 + (y[1] - y[2])**2)\n",
        "    \n",
        "    # Compute accelerations\n",
        "    ax = np.zeros(3)\n",
        "    ay = np.zeros(3)\n",
        "    ax[0] = G * (masses[1] * (x[1] - x[0]) / r12**3 + masses[2] * (x[2] - x[0]) / r13**3)\n",
        "    ay[0] = G * (masses[1] * (y[1] - y[0]) / r12**3 + masses[2] * (y[2] - y[0]) / r13**3)\n",
        "    ax[1] = G * (masses[0] * (x[0] - x[1]) / r12**3 + masses[2] * (x[2] - x[1]) / r23**3)\n",
        "    ay[1] = G * (masses[0] * (y[0] - y[1]) / r12**3 + masses[2] * (y[2] - y[1]) / r23**3)\n",
        "    ax[2] = G * (masses[0] * (x[0] - x[2]) / r13**3 + masses[1] * (x[1] - x[2]) / r23**3)\n",
        "    ay[2] = G * (masses[0] * (y[0] - y[2]) / r13**3 + masses[1] * (y[1] - y[2]) / r23**3)\n",
        "\n",
        "    # Update positions and velocities\n",
        "    x += h * vx\n",
        "    y += h * vy\n",
        "    vx += h * ax\n",
        "    vy += h * ay\n",
        "    \n",
        "    return x, y, vx, vy, ax, ay\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import math\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Define the initial conditions\n",
        "h = 0.003\n",
        "t = 0.0\n",
        "x = np.array([1, -0.5, -0.5])\n",
        "y = np.array([0, math.sqrt(3)/2, -math.sqrt(3)/2])\n",
        "v = np.sqrt(1 / np.sqrt(3))\n",
        "vx = np.zeros(3)\n",
        "vy = np.zeros(3)\n",
        "vx[0] = 0\n",
        "vy[0] = v\n",
        "vx[1] = -math.sqrt(3) / 2 * v\n",
        "vx[2] = math.sqrt(3) / 2 * v\n",
        "vy[1] = -0.5 * v\n",
        "vy[2] = -0.5 * v\n",
        "masses = np.array([1.0, 1.0, 1.0])\n",
        "\n",
        "# Define the number of time steps to simulate\n",
        "num_steps = 5000\n",
        "\n",
        "# Define a list to store the positions of the stars\n",
        "pos = np.zeros((num_steps+1, 3, 2))\n",
        "pos[0,:,0] = x\n",
        "pos[0,:,1] = y\n",
        "\n",
        "# Simulate the system and store the positions of the stars\n",
        "for step in range(num_steps):\n",
        "    x, y, vx, vy, _, _ = forward_euler_step(h, x, y, vx, vy, masses)\n",
        "    pos[step+1,:,0] = x\n",
        "    pos[step+1,:,1] = y\n",
        "\n",
        "# Plot the trajectories of the stars\n",
        "fig, ax = plt.subplots(figsize=(6,6))\n",
        "plt.plot(pos[:,0,0], pos[:,0,1], 'r', label='Star 1')\n",
        "plt.plot(pos[:,1,0], pos[:,1,1], 'g', label='Star 2')\n",
        "plt.plot(pos[:,2,0], pos[:,2,1], 'b', label='Star 3')\n",
        "plt.legend()\n",
        "plt.xlabel('x')\n",
        "plt.ylabel('y')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "GYDYv-7WbyF-",
        "outputId": "391cfb71-e72d-4df6-90e2-f536ca271bde"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "import torch.nn as nn\n",
        "import torch.nn.functional as F\n",
        "\n",
        "class Actor(nn.Module):\n",
        "    def __init__(self, state_dim, action_dim, max_action):\n",
        "        super(Actor, self).__init__()\n",
        "\n",
        "        self.l1 = nn.Linear(state_dim, 300)\n",
        "        self.l2 = nn.Linear(300, 300)\n",
        "        self.l3 = nn.Linear(300, action_dim)\n",
        "        self.max_action = max_action\n",
        "\n",
        "    def forward(self, state):\n",
        "        a = F.relu(self.l1(state))\n",
        "        # a = F.relu(self.l2(a))\n",
        "        a = torch.sigmoid(self.l3(a)) * self.max_action\n",
        "        return a\n",
        "\n",
        "\n",
        "class Critic(nn.Module):\n",
        "    def __init__(self, state_dim, action_dim):\n",
        "        super(Critic, self).__init__()\n",
        "\n",
        "        self.l1 = nn.Linear(state_dim + action_dim, 300)\n",
        "        self.l2 = nn.Linear(300, 300)\n",
        "        self.l3 = nn.Linear(300, 1)\n",
        "\n",
        "    def forward(self, state, action):\n",
        "        q = F.relu(self.l1(torch.cat([state, action], 1)))\n",
        "        # q = F.relu(self.l2(q))\n",
        "        return self.l3(q)\n"
      ],
      "metadata": {
        "id": "xTFBq4uwfELU"
      },
      "execution_count": 72,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class DDPG(object):\n",
        "    def __init__(self, state_dim, action_dim, max_action):\n",
        "        self.actor = Actor(state_dim, action_dim, max_action)\n",
        "        self.actor_target = Actor(state_dim, action_dim, max_action)\n",
        "        self.actor_target.load_state_dict(self.actor.state_dict())\n",
        "        self.actor_optimizer = torch.optim.Adam(self.actor.parameters())\n",
        "        \n",
        "        self.critic = Critic(state_dim, action_dim)\n",
        "        self.critic_target = Critic(state_dim, action_dim)\n",
        "        self.critic_target.load_state_dict(self.critic.state_dict())\n",
        "        self.critic_optimizer = torch.optim.Adam(self.critic.parameters())\n",
        "        \n",
        "        self.max_action = max_action\n",
        "\n",
        "    def select_action(self, state):\n",
        "        state = torch.Tensor(state.reshape(1, -1))\n",
        "        return self.actor(state).cpu().data.numpy().flatten()\n",
        "\n",
        "    def train(self, replay_buffer, iterations, batch_size=64, discount=0.999, tau=0.005):\n",
        "        for it in range(iterations):\n",
        "            # Sample replay buffer\n",
        "            x, y, u, r, d = replay_buffer.sample(batch_size)\n",
        "            state = torch.Tensor(x)\n",
        "            action = torch.Tensor(u)\n",
        "            next_state = torch.Tensor(y)\n",
        "            done = torch.Tensor(1 - d)\n",
        "            reward = torch.Tensor(r)\n",
        "\n",
        "            # Compute the target Q value\n",
        "            target_Q = self.critic_target(next_state, self.actor_target(next_state))\n",
        "            target_Q = reward + (done * discount * target_Q).detach()\n",
        "\n",
        "            # Get current Q estimate\n",
        "            current_Q = self.critic(state, action)\n",
        "\n",
        "            # Compute critic loss\n",
        "            critic_loss = F.mse_loss(current_Q, target_Q)\n",
        "\n",
        "            # Optimize the critic\n",
        "            self.critic_optimizer.zero_grad()\n",
        "            critic_loss.backward()\n",
        "            self.critic_optimizer.step()\n",
        "\n",
        "            # Compute actor loss\n",
        "            actor_loss = -self.critic(state, self.actor(state)).mean()\n",
        "\n",
        "            # Optimize the actor\n",
        "            self.actor_optimizer.zero_grad()\n",
        "            actor_loss.backward()\n",
        "            self.actor_optimizer.step()\n",
        "\n",
        "            # Update the frozen target models\n",
        "            for param, target_param in zip(self.critic.parameters(), self.critic_target.parameters()):\n",
        "                target_param.data.copy_(tau * param.data + (1 - tau) * target_param.data)\n",
        "\n",
        "            for param, target_param in zip(self.actor.parameters(), self.actor_target.parameters()):\n",
        "                target_param.data.copy_(tau * param.data + (1 - tau) * target_param.data)\n"
      ],
      "metadata": {
        "id": "-_qxVZbD9ljY"
      },
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "class ReplayBuffer(object):\n",
        "    def __init__(self, max_size=1e6):\n",
        "        self.storage = []\n",
        "        self.max_size = max_size\n",
        "        self.ptr = 0\n",
        "\n",
        "    def add(self, transition):\n",
        "        if len(self.storage) == self.max_size:\n",
        "            self.storage[int(self.ptr)] = transition\n",
        "            self.ptr = (self.ptr + 1) % self.max_size\n",
        "        else:\n",
        "            self.storage.append(transition)\n",
        "\n",
        "    def sample(self, batch_size):\n",
        "        ind = np.random.randint(0, len(self.storage), size=batch_size)\n",
        "        batch_states, batch_next_states, batch_actions, batch_rewards, batch_dones = [], [], [], [], []\n",
        "        for i in ind: \n",
        "            state, next_state, action, reward, done = self.storage[i]\n",
        "            batch_states.append(np.array(state, copy=False))\n",
        "            batch_next_states.append(np.array(next_state, copy=False))\n",
        "            batch_actions.append(np.array(action, copy=False))\n",
        "            batch_rewards.append(np.array(reward, copy=False))\n",
        "            batch_dones.append(np.array(done, copy=False))\n",
        "        return np.array(batch_states), np.array(batch_next_states), np.array(batch_actions), np.array(batch_rewards).reshape(-1, 1), np.array(batch_dones).reshape(-1, 1)\n"
      ],
      "metadata": {
        "id": "ICR3awjNC7EI"
      },
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "### environment wrapper functions\n",
        "\n",
        "def reset_environment():\n",
        "    x = np.array([1, -0.5, -0.5])\n",
        "    y = np.array([0, math.sqrt(3)/2, -math.sqrt(3)/2])\n",
        "    v = np.sqrt(1 / np.sqrt(3))\n",
        "    vx = np.zeros(3)\n",
        "    vy = np.zeros(3)\n",
        "    vx[0] = 0\n",
        "    vy[0] = v\n",
        "    vx[1] = -math.sqrt(3) / 2 * v\n",
        "    vx[2] = math.sqrt(3) / 2 * v\n",
        "    vy[1] = -0.5 * v\n",
        "    vy[2] = -0.5 * v\n",
        "    return (np.concatenate((x,y,vx,vy,np.zeros(6))))"
      ],
      "metadata": {
        "id": "72ZKmWGf-Okb"
      },
      "execution_count": 75,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "### environment wrapper functions\n",
        "\n",
        "def step_environment(state, action):\n",
        "    \"\"\"\n",
        "    input:\n",
        "        state(np.ndarray(18)): array of x,y,vx,vy,ax,ay\n",
        "        action(np.ndarray(6)): array of perturbations to x and y\n",
        "    return:\n",
        "        state(np.ndarray(18)): array of x,y,vx,vy,ax,ay\n",
        "        reward: 0.05 - deviation from circular orbit\n",
        "        done: if deviation exceeds 0.05\n",
        "    \"\"\"\n",
        "    x = state[:3] + action[:3]\n",
        "    y = state[3:6] + action[3:]\n",
        "    vx = state[6:9]\n",
        "    vy = state[9:12]\n",
        "    masses = np.ones(3)\n",
        "    h = 0.003\n",
        "    done = False\n",
        "    # we run 10 steps of numerical simulation for each environment step to reduce \n",
        "    # complexity\n",
        "    time_steps = 10 \n",
        "    for i in range(time_steps):\n",
        "        x, y, vx, vy, ax, ay = forward_euler_step(h, x, y, vx, vy, masses)\n",
        "        #average deviation from circular orbit\n",
        "        deviation = np.sum(np.abs(1-np.sum(np.square(np.concatenate((x,y)).reshape((2,3))), axis = 0)))/3\n",
        "        #print (deviation)\n",
        "        #print (x,y)\n",
        "        #print (distance)\n",
        "        if deviation > 0.05:\n",
        "            done = True\n",
        "            #print (\"deviation when loop broke:\", deviation)\n",
        "            break\n",
        "    \n",
        "    return np.concatenate((x, y, vx, vy, ax, ay)), 0.05 - deviation, done\n"
      ],
      "metadata": {
        "id": "xk4JozVc-sgS"
      },
      "execution_count": 85,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q_VkT_vkhqXZ",
        "outputId": "2f3569bf-3aea-4de8-bba7-ecc37ddfdf31"
      },
      "execution_count": 68,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.0004703691263170384\n",
            "0.0007761907270641041\n",
            "0.0004917183182191845\n",
            "0.0008863087282425056\n",
            "0.0013225274046712403\n",
            "0.0016111083031580264\n",
            "0.0014249949292792774\n",
            "0.0011354578677840177\n",
            "0.0012749440241872263\n",
            "0.0011653374604517763\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "state_dim = 18 #x,y, vx, vy, ax, ay for 3 stars each\n",
        "action_dim = 6 #x,y \n",
        "max_action = 1e-3\n",
        "\n",
        "# Initialize the agent and the replay buffer\n",
        "agent = DDPG(state_dim, action_dim, max_action)\n",
        "replay_buffer = ReplayBuffer()\n",
        "\n",
        "# Specify the number of time steps to simulate\n",
        "num_steps = 1000\n",
        "num_episodes = 500\n",
        "\n",
        "episode_rewards = []\n",
        "episode_steps = []\n",
        "\n",
        "# Iterate over the number of episodes\n",
        "for episode in range(num_episodes):\n",
        "\n",
        "    # Reset the state, done flag, and episode reward\n",
        "    state = reset_environment()\n",
        "    done = False\n",
        "    episode_reward = 0\n",
        "\n",
        "    # Iterate over the maximum length of an episode\n",
        "    for step in range(num_steps):\n",
        "\n",
        "        # Select action\n",
        "        action = agent.select_action(state)\n",
        "\n",
        "        # Take a step in the environment\n",
        "        next_state, reward, done = step_environment(state, action)\n",
        "\n",
        "        # Store the transition in the replay buffer\n",
        "        replay_buffer.add((state, next_state, action, reward, done))\n",
        "\n",
        "        # Move to the next state\n",
        "        state = next_state\n",
        "\n",
        "        # Update the total episode reward\n",
        "        episode_reward += reward\n",
        "\n",
        "        # If the episode is done, break from the loop\n",
        "        if done:\n",
        "            \n",
        "            break\n",
        "\n",
        "    # Train the agent\n",
        "    agent.train(replay_buffer, episode)\n",
        "\n",
        "    # Print the total episode reward\n",
        "    print('Episode {}: {}, {}'.format(episode, episode_reward, step))\n",
        "\n",
        "    # Store the total episode reward and steps\n",
        "    episode_rewards.append(episode_reward)\n",
        "    episode_steps.append(step)\n",
        "\n",
        "# Plot the episode rewards\n",
        "plt.figure(figsize=(10,5))\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.plot(range(num_episodes), episode_rewards)\n",
        "plt.xlabel('Episode')\n",
        "plt.ylabel('Total Reward')\n",
        "\n",
        "# Plot the episode steps\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.plot(range(num_episodes), episode_steps)\n",
        "plt.xlabel('Episode')\n",
        "plt.ylabel('Steps')\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "DrimjWWy9sFX",
        "outputId": "ac5630e0-e020-40b5-d2d8-5c5ac2828912"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Episode 0: 6.890005064448506, 201\n",
            "Episode 1: 7.877298956099992, 279\n",
            "Episode 2: 4.291477955710988, 160\n",
            "Episode 3: 6.973849616434087, 193\n",
            "Episode 4: 5.8496180669817806, 179\n",
            "Episode 5: 5.010302603782281, 154\n",
            "Episode 6: 3.0898568836730855, 104\n",
            "Episode 7: 3.0912982441359005, 92\n",
            "Episode 8: 4.711609270961828, 176\n",
            "Episode 9: 2.515032472355624, 83\n",
            "Episode 10: 4.007044593833956, 140\n",
            "Episode 11: 3.1077601851463097, 126\n",
            "Episode 12: 3.862087230850105, 169\n",
            "Episode 13: 2.6058331717874665, 86\n",
            "Episode 14: 3.849822748725005, 171\n",
            "Episode 15: 3.6258878810556223, 144\n",
            "Episode 16: 1.7771829656817908, 59\n",
            "Episode 17: 1.895584429385614, 81\n",
            "Episode 18: 1.8570338456013151, 64\n",
            "Episode 19: 1.7552204546418766, 60\n",
            "Episode 20: 1.436316289474478, 57\n",
            "Episode 21: 2.2475808803084836, 78\n",
            "Episode 22: 1.9439278020828796, 63\n",
            "Episode 23: 1.5323556470229909, 61\n",
            "Episode 24: 1.546900996723109, 53\n",
            "Episode 25: 1.72818385201794, 59\n",
            "Episode 26: 1.813364978215595, 69\n",
            "Episode 27: 1.4333000077724267, 61\n",
            "Episode 28: 1.3534691928386442, 50\n",
            "Episode 29: 2.1588348776363873, 72\n",
            "Episode 30: 2.213622865676796, 69\n",
            "Episode 31: 1.1576679898509423, 42\n",
            "Episode 32: 1.3272946402800372, 47\n",
            "Episode 33: 1.3195147172111572, 57\n",
            "Episode 34: 6.166012036769317, 181\n",
            "Episode 35: 1.7265272499728488, 73\n",
            "Episode 36: 1.6177282922099578, 61\n",
            "Episode 37: 1.8644329504148887, 75\n",
            "Episode 38: 2.119451790591828, 71\n",
            "Episode 39: 1.9032767514752085, 58\n",
            "Episode 40: 1.6119434686373415, 68\n",
            "Episode 41: 2.0354057493745, 65\n",
            "Episode 42: 1.652725881600325, 59\n",
            "Episode 43: 1.607043265271378, 53\n",
            "Episode 44: 1.676402359226081, 57\n",
            "Episode 45: 1.7205644594424365, 68\n",
            "Episode 46: 1.7841709510840575, 57\n",
            "Episode 47: 1.9549729306044077, 60\n",
            "Episode 48: 1.961409810600828, 82\n",
            "Episode 49: 1.7684078579723128, 61\n",
            "Episode 50: 2.088065682051523, 73\n",
            "Episode 51: 1.9084231863929595, 68\n",
            "Episode 52: 2.399542666744091, 70\n",
            "Episode 53: 2.190972712329693, 65\n",
            "Episode 54: 2.2607037714625555, 87\n",
            "Episode 55: 1.752386843424397, 59\n",
            "Episode 56: 1.4165272848895936, 49\n",
            "Episode 57: 2.11496166784118, 71\n",
            "Episode 58: 1.763044884184417, 66\n",
            "Episode 59: 2.0550266725394937, 92\n",
            "Episode 60: 1.5984272378429096, 63\n",
            "Episode 61: 2.731124249197424, 114\n",
            "Episode 62: 1.7379410205220276, 73\n",
            "Episode 63: 1.7837072615954805, 69\n",
            "Episode 64: 2.5367456139118825, 120\n",
            "Episode 65: 2.0724816677602704, 112\n",
            "Episode 66: 2.602255206044763, 100\n",
            "Episode 67: 1.9045317825789574, 78\n",
            "Episode 68: 2.4923013645358214, 104\n",
            "Episode 69: 2.238822594519109, 79\n",
            "Episode 70: 2.0380011372889553, 69\n",
            "Episode 71: 2.8655797320742074, 133\n",
            "Episode 72: 3.052956399348237, 131\n",
            "Episode 73: 2.6636849762500527, 114\n",
            "Episode 74: 3.8260459078208333, 174\n",
            "Episode 75: 2.34296412799911, 89\n",
            "Episode 76: 2.3370030076218793, 85\n",
            "Episode 77: 2.4354422679192167, 114\n",
            "Episode 78: 2.351068446331149, 92\n",
            "Episode 79: 2.6426882903272615, 113\n",
            "Episode 80: 1.8866362610592715, 73\n",
            "Episode 81: 2.261624199842669, 119\n",
            "Episode 82: 2.048296039887388, 83\n",
            "Episode 83: 1.6989153496554297, 82\n",
            "Episode 84: 3.2537887440714974, 132\n",
            "Episode 85: 2.7184065766360845, 118\n",
            "Episode 86: 2.6344092298742487, 144\n",
            "Episode 87: 2.2082232762961413, 82\n",
            "Episode 88: 2.638413113948046, 86\n",
            "Episode 89: 2.3580904358415444, 77\n",
            "Episode 90: 1.8695207132790483, 74\n",
            "Episode 91: 2.3570730076311843, 91\n",
            "Episode 92: 1.484896594795446, 97\n",
            "Episode 93: 2.7504455587462435, 102\n",
            "Episode 94: 2.554790801876543, 91\n",
            "Episode 95: 2.4719203645178944, 87\n",
            "Episode 96: 2.050505954863626, 72\n",
            "Episode 97: 2.1548912111921497, 82\n",
            "Episode 98: 2.526732154019024, 120\n",
            "Episode 99: 2.605035707226453, 93\n",
            "Episode 100: 4.595416319162448, 197\n",
            "Episode 101: 2.956670967536725, 100\n",
            "Episode 102: 2.2551409306949672, 86\n",
            "Episode 103: 1.916010533085006, 67\n",
            "Episode 104: 1.384976729558421, 79\n",
            "Episode 105: 2.1347112109486788, 82\n",
            "Episode 106: 2.072074101649239, 79\n",
            "Episode 107: 2.129214686564423, 81\n",
            "Episode 108: 1.9813523919428506, 62\n",
            "Episode 109: 2.3164125562268603, 94\n",
            "Episode 110: 2.2198329713988665, 86\n",
            "Episode 111: 2.501896891695965, 91\n",
            "Episode 112: 2.1473840110134588, 86\n",
            "Episode 113: 2.697203862396406, 103\n",
            "Episode 114: 2.7149504857094815, 108\n",
            "Episode 115: 2.220901739080401, 83\n",
            "Episode 116: 1.7835525107660952, 69\n",
            "Episode 117: 1.9613169453574046, 80\n",
            "Episode 118: 3.3627236150916855, 115\n",
            "Episode 119: 2.6571896325426128, 103\n",
            "Episode 120: 2.2355500529915378, 98\n",
            "Episode 121: 2.109379351564424, 78\n",
            "Episode 122: 2.7985430694740705, 99\n",
            "Episode 123: 2.439123362024207, 95\n",
            "Episode 124: 1.7243172214860005, 61\n",
            "Episode 125: 1.3729352874513117, 50\n",
            "Episode 126: 1.2885808878296947, 51\n",
            "Episode 127: 2.002783970181153, 70\n",
            "Episode 128: 1.8792277946550358, 70\n",
            "Episode 129: 1.7181839275237567, 61\n",
            "Episode 130: 1.6291083854259618, 54\n",
            "Episode 131: 1.5160930990330574, 56\n",
            "Episode 132: 1.5744181108062651, 60\n",
            "Episode 133: 1.7176288120381664, 61\n",
            "Episode 134: 1.7724171033267917, 57\n",
            "Episode 135: 2.07917940792793, 73\n",
            "Episode 136: 1.9976312080049934, 68\n",
            "Episode 137: 1.57418061291727, 56\n",
            "Episode 138: 1.6884269144283566, 57\n",
            "Episode 139: 1.6025381498741678, 57\n",
            "Episode 140: 1.9289685682719822, 65\n",
            "Episode 141: 1.9880229889567784, 66\n",
            "Episode 142: 2.155187665960537, 70\n",
            "Episode 143: 1.9158862633731384, 69\n",
            "Episode 144: 1.5869905828441606, 55\n",
            "Episode 145: 2.0214097741980255, 66\n",
            "Episode 146: 1.9213401800701269, 61\n",
            "Episode 147: 1.9849624876873262, 73\n",
            "Episode 148: 1.9455163443313679, 73\n",
            "Episode 149: 2.2221780917036162, 72\n",
            "Episode 150: 1.6302782610342244, 66\n",
            "Episode 151: 1.414537125761095, 58\n",
            "Episode 152: 1.3985499978047187, 68\n",
            "Episode 153: 2.0963414998116967, 75\n",
            "Episode 154: 1.9295942580579264, 70\n",
            "Episode 155: 1.6256332391518138, 62\n",
            "Episode 156: 1.5844843154149675, 65\n",
            "Episode 157: 2.5246658044270935, 81\n",
            "Episode 158: 2.0391086100840004, 74\n",
            "Episode 159: 1.91615776027183, 60\n",
            "Episode 160: 1.6806471519371755, 60\n",
            "Episode 161: 1.9760943519701133, 67\n",
            "Episode 162: 1.9958888646707211, 82\n",
            "Episode 163: 2.070603481858301, 71\n",
            "Episode 164: 2.035197589989289, 56\n",
            "Episode 165: 1.9488808793339714, 58\n",
            "Episode 166: 1.736034643928969, 56\n",
            "Episode 167: 1.8860553275344263, 60\n",
            "Episode 168: 1.752053806768953, 53\n",
            "Episode 169: 1.5735193501057703, 49\n",
            "Episode 170: 1.8562994769721248, 56\n",
            "Episode 171: 1.9524326475356342, 57\n",
            "Episode 172: 1.8317714274274424, 55\n",
            "Episode 173: 1.8537504699625862, 53\n",
            "Episode 174: 2.140823545659012, 80\n",
            "Episode 175: 2.2728932444340844, 83\n",
            "Episode 176: 2.3092896695347727, 79\n",
            "Episode 177: 2.450717917630809, 81\n",
            "Episode 178: 2.0919419799202736, 79\n",
            "Episode 179: 1.6800220913053692, 59\n",
            "Episode 180: 1.5360202997882526, 57\n",
            "Episode 181: 1.7616310384555351, 64\n",
            "Episode 182: 2.5718005487440934, 94\n",
            "Episode 183: 2.9067778444279275, 85\n",
            "Episode 184: 1.682268598362775, 59\n",
            "Episode 185: 1.5856176357936593, 50\n",
            "Episode 186: 1.5387840193439788, 66\n",
            "Episode 187: 1.5521079635572057, 55\n",
            "Episode 188: 1.5959613141186135, 51\n",
            "Episode 189: 1.8665448165025773, 63\n",
            "Episode 190: 2.7717604826914983, 102\n",
            "Episode 191: 3.091820223611624, 115\n",
            "Episode 192: 2.1622185670369363, 78\n",
            "Episode 193: 2.691060380980318, 99\n",
            "Episode 194: 3.7882649582429795, 134\n",
            "Episode 195: 3.574175740345955, 125\n",
            "Episode 196: 5.134119343990954, 173\n",
            "Episode 197: 2.985525700820044, 109\n",
            "Episode 198: 3.888784765413776, 126\n",
            "Episode 199: 3.2324237506557107, 122\n",
            "Episode 200: 3.293793756126286, 119\n",
            "Episode 201: 3.4403910873852688, 131\n",
            "Episode 202: 4.89166520642305, 157\n",
            "Episode 203: 3.716651029583358, 133\n",
            "Episode 204: 2.8323931101453463, 108\n",
            "Episode 205: 4.096898948905908, 125\n",
            "Episode 206: 4.519037656561134, 132\n",
            "Episode 207: 2.8172363074638294, 124\n",
            "Episode 208: 4.289113268412887, 147\n",
            "Episode 209: 4.113687877250369, 146\n",
            "Episode 210: 3.5849741304192415, 120\n",
            "Episode 211: 5.28821042601048, 167\n",
            "Episode 212: 4.026561269229029, 118\n",
            "Episode 213: 4.987517603569235, 192\n",
            "Episode 214: 4.067979820873299, 133\n",
            "Episode 215: 3.7269370084159457, 115\n",
            "Episode 216: 4.241315405445463, 124\n",
            "Episode 217: 4.1117461616248105, 128\n",
            "Episode 218: 3.12518171320162, 136\n",
            "Episode 219: 6.386399564201882, 206\n",
            "Episode 220: 6.656358215900222, 181\n",
            "Episode 221: 4.204304361824625, 120\n",
            "Episode 222: 3.755554542538047, 130\n",
            "Episode 223: 5.973056495652787, 190\n",
            "Episode 224: 6.278800653819912, 187\n",
            "Episode 225: 2.9952028619171585, 119\n",
            "Episode 226: 4.954268928064207, 165\n",
            "Episode 227: 4.174504751108113, 159\n",
            "Episode 228: 4.012859311758907, 146\n",
            "Episode 229: 4.271448375568123, 143\n",
            "Episode 230: 3.0251470916503105, 137\n",
            "Episode 231: 4.191957617072602, 139\n",
            "Episode 232: 4.177061771159331, 123\n",
            "Episode 233: 5.200590888064619, 199\n",
            "Episode 234: 3.649354012848698, 127\n",
            "Episode 235: 4.563236106431569, 162\n",
            "Episode 236: 3.734794442282725, 124\n",
            "Episode 237: 5.864313213960744, 205\n",
            "Episode 238: 5.720512578748908, 190\n",
            "Episode 239: 9.303820192975936, 256\n",
            "Episode 240: 6.695150198630731, 222\n",
            "Episode 241: 3.19166631157856, 130\n",
            "Episode 242: 4.118391200232884, 148\n",
            "Episode 243: 3.3247882990875177, 111\n",
            "Episode 244: 9.012121908783028, 264\n",
            "Episode 245: 4.539072312869092, 142\n",
            "Episode 246: 4.420267740229699, 121\n",
            "Episode 247: 4.019376741907334, 154\n",
            "Episode 248: 7.7188199599691885, 236\n",
            "Episode 249: 3.5352562326405446, 128\n",
            "Episode 250: 3.595773322056677, 108\n",
            "Episode 251: 3.9942824189397097, 144\n",
            "Episode 252: 5.045656990094306, 163\n",
            "Episode 253: 5.237692027677723, 187\n",
            "Episode 254: 4.9335738813850885, 144\n",
            "Episode 255: 4.218384757603845, 109\n",
            "Episode 256: 4.335083753031296, 167\n",
            "Episode 257: 4.019661367650292, 130\n",
            "Episode 258: 4.386353675496877, 140\n",
            "Episode 259: 4.8956901901364285, 148\n",
            "Episode 260: 5.674380550678325, 194\n",
            "Episode 261: 5.457971110500647, 178\n",
            "Episode 262: 3.830421554856677, 108\n",
            "Episode 263: 4.51911051947785, 121\n",
            "Episode 264: 4.277717335185244, 134\n",
            "Episode 265: 3.372068841324301, 128\n",
            "Episode 266: 2.3160067214115307, 118\n",
            "Episode 267: 4.1909709383573635, 141\n",
            "Episode 268: 3.37769606654832, 145\n",
            "Episode 269: 4.276661321355835, 144\n",
            "Episode 270: 4.479743252202832, 169\n",
            "Episode 271: 4.726422074413017, 134\n",
            "Episode 272: 3.2656263884631604, 152\n",
            "Episode 273: 5.3775460083677, 204\n",
            "Episode 274: 3.8252744185396828, 137\n",
            "Episode 275: 4.3044624725254526, 140\n",
            "Episode 276: 2.712857541489416, 134\n",
            "Episode 277: 4.696808854368431, 142\n",
            "Episode 278: 5.320330469957684, 182\n",
            "Episode 279: 3.3774956880857765, 142\n",
            "Episode 280: 2.9592150078810313, 98\n",
            "Episode 281: 4.426412642894135, 115\n",
            "Episode 282: 3.182651018296005, 106\n",
            "Episode 283: 4.449117598992637, 138\n",
            "Episode 284: 3.6696335199756183, 141\n",
            "Episode 285: 3.234232892272597, 112\n",
            "Episode 286: 6.582943477072828, 178\n",
            "Episode 287: 4.85552565404056, 144\n",
            "Episode 288: 2.69471043050051, 109\n",
            "Episode 289: 3.4622764835963973, 139\n",
            "Episode 290: 4.01770328663632, 127\n",
            "Episode 291: 2.5866665049509034, 110\n",
            "Episode 292: 2.473789696319421, 101\n",
            "Episode 293: 2.4895426337046667, 100\n",
            "Episode 294: 3.525877114842583, 122\n",
            "Episode 295: 4.916739982684647, 164\n",
            "Episode 296: 6.304528170856504, 211\n",
            "Episode 297: 4.494510210805783, 181\n",
            "Episode 298: 2.7990923975069086, 103\n",
            "Episode 299: 4.079416648076137, 147\n",
            "Episode 300: 3.9001875868354614, 128\n",
            "Episode 301: 4.760881840001124, 173\n",
            "Episode 302: 3.0599552915200703, 133\n",
            "Episode 303: 5.21854493750931, 199\n",
            "Episode 304: 4.6045986279906215, 179\n",
            "Episode 305: 2.347392004584676, 105\n",
            "Episode 306: 2.906647083940134, 113\n",
            "Episode 307: 5.456884891253464, 198\n",
            "Episode 308: 8.788327656894051, 297\n",
            "Episode 309: 3.0631885121329487, 124\n",
            "Episode 310: 3.6343920995778083, 148\n",
            "Episode 311: 3.2531631831894354, 121\n",
            "Episode 312: 2.1669601729541244, 87\n",
            "Episode 313: 3.509824385318274, 150\n",
            "Episode 314: 5.962357004321689, 211\n",
            "Episode 315: 3.584893727186855, 154\n",
            "Episode 316: 4.046671336856018, 144\n",
            "Episode 317: 5.574982259198357, 164\n",
            "Episode 318: 3.0107060331488427, 112\n",
            "Episode 319: 2.3851192560508685, 119\n",
            "Episode 320: 4.136948729656099, 149\n",
            "Episode 321: 4.673007725085949, 188\n",
            "Episode 322: 4.201824000831426, 192\n",
            "Episode 323: 4.692969326374795, 182\n",
            "Episode 324: 2.67256045820244, 103\n",
            "Episode 325: 3.353697537562469, 136\n",
            "Episode 326: 3.280183732244785, 133\n",
            "Episode 327: 3.998567282192412, 145\n",
            "Episode 328: 4.572031112362007, 179\n",
            "Episode 329: 5.479428628590801, 204\n",
            "Episode 330: 5.555560217871037, 185\n",
            "Episode 331: 3.3124080343283673, 134\n",
            "Episode 332: 5.83843012165613, 208\n",
            "Episode 333: 2.540573668175904, 93\n",
            "Episode 334: 2.0184858252272293, 72\n",
            "Episode 335: 5.9727931124458555, 168\n",
            "Episode 336: 4.574955096680126, 150\n",
            "Episode 337: 2.521873640619897, 106\n",
            "Episode 338: 5.279858021735845, 216\n",
            "Episode 339: 3.2624477088599333, 117\n",
            "Episode 340: 3.9407669178488365, 138\n",
            "Episode 341: 5.750407193672784, 188\n",
            "Episode 342: 3.492190578646747, 123\n",
            "Episode 343: 5.947788365187554, 225\n",
            "Episode 344: 4.435384760172155, 177\n",
            "Episode 345: 2.99446032986319, 128\n",
            "Episode 346: 4.26798566601867, 138\n",
            "Episode 347: 3.835201442831453, 142\n",
            "Episode 348: 3.9721907630183764, 170\n",
            "Episode 349: 1.4510589277140185, 62\n",
            "Episode 350: 6.055982498772045, 211\n",
            "Episode 351: 4.156853302541231, 143\n",
            "Episode 352: 4.034501806308027, 155\n",
            "Episode 353: 3.650324881008944, 137\n",
            "Episode 354: 5.406154062981642, 200\n",
            "Episode 355: 3.317596107910158, 138\n",
            "Episode 356: 3.064047183248572, 112\n",
            "Episode 357: 3.059597159939414, 118\n",
            "Episode 358: 4.003689349420188, 125\n",
            "Episode 359: 4.500411995862911, 185\n",
            "Episode 360: 5.428690822118591, 174\n",
            "Episode 361: 3.459426058487904, 129\n",
            "Episode 362: 8.054684720143655, 219\n",
            "Episode 363: 4.572751321412229, 152\n",
            "Episode 364: 3.793915650972906, 150\n",
            "Episode 365: 3.734211098118872, 142\n",
            "Episode 366: 2.664582182903203, 117\n",
            "Episode 367: 3.2910906140530116, 139\n",
            "Episode 368: 5.511076069066991, 205\n",
            "Episode 369: 6.107740257927639, 238\n",
            "Episode 370: 6.727847828780242, 237\n",
            "Episode 371: 3.3347693401455003, 125\n",
            "Episode 372: 6.374913191046345, 204\n",
            "Episode 373: 3.4006525997443724, 134\n",
            "Episode 374: 4.540132151143526, 179\n",
            "Episode 375: 7.405900008531432, 222\n",
            "Episode 376: 6.4571534755994415, 234\n",
            "Episode 377: 5.662399403531788, 170\n",
            "Episode 378: 3.491159712411234, 145\n",
            "Episode 379: 7.255400681971661, 216\n",
            "Episode 380: 4.879425176202437, 153\n",
            "Episode 381: 4.706532245591245, 161\n",
            "Episode 382: 5.30426277720479, 159\n",
            "Episode 383: 5.366753318332844, 173\n",
            "Episode 384: 3.846680596518457, 117\n",
            "Episode 385: 4.783196580316513, 166\n",
            "Episode 386: 5.608924254855305, 196\n",
            "Episode 387: 4.749177662512452, 168\n",
            "Episode 388: 4.681014151133689, 173\n",
            "Episode 389: 5.017965987655505, 180\n",
            "Episode 390: 4.94668443669094, 194\n",
            "Episode 391: 5.012843574638846, 171\n",
            "Episode 392: 5.447243493344719, 223\n",
            "Episode 393: 10.053367683366012, 278\n",
            "Episode 394: 2.5386172149107287, 92\n",
            "Episode 395: 4.329436246415762, 157\n",
            "Episode 396: 3.8051988608213274, 152\n",
            "Episode 397: 3.883155060616871, 159\n",
            "Episode 398: 4.883838694867291, 186\n",
            "Episode 399: 4.4090227723908875, 153\n",
            "Episode 400: 5.4319689694342905, 195\n",
            "Episode 401: 6.126687722035318, 253\n",
            "Episode 402: 3.5552398043798266, 135\n",
            "Episode 403: 4.369373939125462, 155\n",
            "Episode 404: 4.761919192008801, 160\n",
            "Episode 405: 4.352488840328513, 182\n",
            "Episode 406: 5.232079407524159, 172\n",
            "Episode 407: 5.697656190899848, 197\n",
            "Episode 408: 4.914559824196247, 171\n",
            "Episode 409: 6.110792905725575, 233\n",
            "Episode 410: 4.159753882507673, 148\n",
            "Episode 411: 2.670655388505437, 126\n",
            "Episode 412: 3.878755644380577, 166\n",
            "Episode 413: 6.502212754079307, 243\n",
            "Episode 414: 4.528149343545887, 185\n",
            "Episode 415: 3.250615479730178, 108\n",
            "Episode 416: 4.0752287612221085, 159\n",
            "Episode 417: 5.457319787915464, 185\n",
            "Episode 418: 3.404917538465975, 101\n",
            "Episode 419: 4.331217649568269, 172\n",
            "Episode 420: 3.5178206148708133, 137\n",
            "Episode 421: 4.459183659251833, 160\n",
            "Episode 422: 4.129966820032413, 163\n",
            "Episode 423: 4.11749886854272, 160\n",
            "Episode 424: 4.691556607162699, 176\n",
            "Episode 425: 4.6909305383076765, 154\n",
            "Episode 426: 4.4457807855699185, 186\n",
            "Episode 427: 4.289315512804322, 158\n",
            "Episode 428: 2.9293991488981437, 130\n",
            "Episode 429: 4.226427102828569, 145\n",
            "Episode 430: 4.667696488885179, 224\n",
            "Episode 431: 3.9084292404479237, 162\n",
            "Episode 432: 4.121016968394047, 178\n",
            "Episode 433: 3.6748423017617453, 141\n",
            "Episode 434: 4.163268562678187, 141\n",
            "Episode 435: 4.230900357550068, 165\n",
            "Episode 436: 3.0702169197431646, 121\n",
            "Episode 437: 4.501379428805136, 150\n",
            "Episode 438: 4.055254903574243, 138\n",
            "Episode 439: 3.7921956901013814, 131\n",
            "Episode 440: 2.936430784527595, 133\n",
            "Episode 441: 2.2568534158144957, 101\n",
            "Episode 442: 4.770927199901419, 147\n",
            "Episode 443: 3.430388502003333, 140\n",
            "Episode 444: 8.133312642474511, 238\n",
            "Episode 445: 3.8530842746972436, 135\n",
            "Episode 446: 4.295447147012609, 141\n",
            "Episode 447: 4.497495938531362, 161\n",
            "Episode 448: 7.391811427734212, 218\n",
            "Episode 449: 5.0101625276588635, 159\n",
            "Episode 450: 6.31604513312925, 224\n",
            "Episode 451: 3.5873811016973205, 147\n",
            "Episode 452: 3.3976705967113445, 129\n",
            "Episode 453: 4.550946253018327, 172\n",
            "Episode 454: 3.6490880733737114, 145\n",
            "Episode 455: 5.374105390655435, 191\n",
            "Episode 456: 4.98132805306283, 143\n",
            "Episode 457: 4.427169696542826, 159\n",
            "Episode 458: 5.763621702426429, 184\n",
            "Episode 459: 4.2963143787976685, 150\n",
            "Episode 460: 4.246139423482208, 128\n",
            "Episode 461: 5.00631427752215, 182\n",
            "Episode 462: 8.632175817427937, 268\n",
            "Episode 463: 4.912396842554997, 176\n",
            "Episode 464: 2.8995201476897425, 118\n",
            "Episode 465: 5.378318766473269, 186\n",
            "Episode 466: 3.592737272487284, 146\n",
            "Episode 467: 4.351825940723875, 128\n",
            "Episode 468: 2.961878928477686, 113\n",
            "Episode 469: 2.7593401398767434, 108\n",
            "Episode 470: 2.9340488902114963, 111\n",
            "Episode 471: 3.0574976632513384, 118\n",
            "Episode 472: 2.1655923843452967, 94\n",
            "Episode 473: 4.369175221184853, 146\n",
            "Episode 474: 3.1096996395823977, 118\n",
            "Episode 475: 2.920966321076424, 117\n",
            "Episode 476: 1.8886140491788566, 73\n",
            "Episode 477: 2.7180491193368996, 104\n",
            "Episode 478: 2.053993503251798, 105\n",
            "Episode 479: 2.173090058732412, 97\n",
            "Episode 480: 2.7977088556871297, 115\n",
            "Episode 481: 2.102217991744102, 97\n",
            "Episode 482: 3.079291349714087, 117\n",
            "Episode 483: 2.032413095795307, 98\n",
            "Episode 484: 2.2048402062913826, 105\n",
            "Episode 485: 2.7608612981608682, 111\n",
            "Episode 486: 2.9478210911531164, 113\n",
            "Episode 487: 1.7667011846222667, 67\n",
            "Episode 488: 2.0006014399653433, 102\n",
            "Episode 489: 2.808247414272696, 118\n",
            "Episode 490: 2.1309317303463198, 95\n",
            "Episode 491: 2.5090954313745626, 103\n",
            "Episode 492: 3.4565278919268128, 119\n",
            "Episode 493: 2.2371928166184896, 96\n",
            "Episode 494: 2.8668762813677673, 112\n",
            "Episode 495: 2.2380662847851083, 91\n",
            "Episode 496: 4.255193482781415, 161\n",
            "Episode 497: 2.3151344354757044, 116\n",
            "Episode 498: 2.5332987121863195, 91\n",
            "Episode 499: 2.815899510268589, 113\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "\n",
        "# Reset the state, done flag, and episode reward\n",
        "state = reset_environment()\n",
        "done = False\n",
        "\n",
        "# Initialize array to store positions\n",
        "positions = np.zeros((num_steps, 3, 2))\n",
        "\n",
        "# Iterate over the maximum length of an episode\n",
        "for step in range(num_steps):\n",
        "\n",
        "    # Store current positions\n",
        "    positions[step] = state[:6].reshape((2,3)).T\n",
        "\n",
        "    # Select action\n",
        "    action = agent.select_action(state)\n",
        "\n",
        "    # Take a step in the environment\n",
        "    next_state, reward, done = step_environment(state, action)\n",
        "\n",
        "    # Move to the next state\n",
        "    state = next_state\n",
        "\n",
        "    # If the episode is done, break from the loop\n",
        "    if done:\n",
        "        break\n",
        "\n",
        "positions = positions[:step]\n",
        "# Plot the trajectories of the stars\n",
        "fig, ax = plt.subplots(figsize=(6,6))\n",
        "plt.plot(positions[:,0,0], positions[:,0,1], 'r', label='Star 1')\n",
        "plt.plot(positions[:,1,0], positions[:,1,1], 'g', label='Star 2')\n",
        "plt.plot(positions[:,2,0], positions[:,2,1], 'b', label='Star 3')\n",
        "plt.legend()\n",
        "plt.xlabel('x')\n",
        "plt.ylabel('y')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "fQgvnq-R-N1T",
        "outputId": "47b8c5c1-3570-46ea-f0b5-4fa7609aa46e"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 600x600 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "s1qWNTdRZZya"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}