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@nathanmargaglio
Created October 9, 2020 12:36
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DQN Tutorial
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Deep Q-Network"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Build a Deterministic Environment"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import gym\n",
"import time\n",
"import copy\n",
"import threading\n",
"import time\n",
"import collections"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"det_state_trans = []\n",
"for x in range(3):\n",
" state_x = []\n",
" for y in range(3):\n",
" state_y = []\n",
" for a in range(4):\n",
" one_hot = np.zeros(4)\n",
" one_hot[a] = 1\n",
" state_y.append(one_hot)\n",
" state_x.append(state_y)\n",
" det_state_trans.append(state_x)\n",
" \n",
"def get_transition_func(transition_matrix):\n",
" def transition_func(x, y, action, return_probs=False):\n",
" probs = transition_matrix[x][y][action]\n",
" if return_probs:\n",
" return probs\n",
" else:\n",
" return np.random.choice(len(probs), p=probs)\n",
" return transition_func"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"class GridEnvironment(gym.Env):\n",
" metadata = { 'render.modes': ['human'] }\n",
" \n",
" def __init__(self, transition_func, normalize=False):\n",
" self.observation_space = gym.spaces.Box(0, 2, (2,))\n",
" self.action_space = gym.spaces.Discrete(4)\n",
" self.max_timesteps = 5\n",
" self.transition_func = transition_func\n",
" self.normalize = normalize\n",
" \n",
" def _get_distance(self, x, y):\n",
" return abs(x[0] - y[0]) + abs(x[1] - y[1])\n",
" \n",
" def reset(self):\n",
" self.timestep = 0\n",
" self.agent_pos = [0, 0]\n",
" self.goal_pos = [2, 2]\n",
" self.state = np.zeros((3,3))\n",
" self.state[tuple(self.agent_pos)] = 1\n",
" self.state[tuple(self.goal_pos)] = 0.5\n",
" self.prev_distance = self._get_distance(self.agent_pos, self.goal_pos)\n",
" return np.array(self.agent_pos)\n",
" \n",
" def step(self, action):\n",
" action_taken = self.transition_func(self.agent_pos[0], self.agent_pos[1], action)\n",
" self.state = np.random.choice(self.observation_space.shape[0])\n",
" if action_taken == 0:\n",
" self.agent_pos[0] += 1\n",
" if action_taken == 1:\n",
" self.agent_pos[0] -= 1\n",
" if action_taken == 2:\n",
" self.agent_pos[1] += 1\n",
" if action_taken == 3:\n",
" self.agent_pos[1] -= 1\n",
" \n",
" self.agent_pos = np.clip(self.agent_pos, 0, 2)\n",
" self.state = np.zeros((3,3))\n",
" self.state[tuple(self.agent_pos)] = 1\n",
" self.state[tuple(self.goal_pos)] = 0.5\n",
" \n",
" current_distance = self._get_distance(self.agent_pos, self.goal_pos)\n",
" if current_distance < self.prev_distance:\n",
" reward = 1\n",
" elif current_distance > self.prev_distance:\n",
" reward = -1\n",
" else:\n",
" reward = -1\n",
" self.prev_distance = current_distance\n",
" \n",
" self.timestep += 1\n",
" if self.timestep >= self.max_timesteps or current_distance == 0:\n",
" done = True\n",
" else:\n",
" done = False\n",
" info = {}\n",
" \n",
" obs = self.agent_pos\n",
" if self.normalize:\n",
" obs = obs/2.\n",
" return obs, reward, done, info\n",
" \n",
" def render(self, mode='human'):\n",
" plt.imshow(self.state)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype.\u001b[0m\n"
]
},
{
"data": {
"image/png": 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uQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"env = GridEnvironment(get_transition_func(det_state_trans))\n",
"obs = env.reset()\n",
"env.render()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Implement Tabular Method"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"class QLearningAgent:\n",
" def __init__(self, env, epsilon=1.0, lr=0.1, gamma=0.9):\n",
" self.env = env\n",
" self.observation_space = env.observation_space\n",
" self.action_space = env.action_space\n",
" self.q_table = np.zeros((3, 3, 4))\n",
" self.epsilon = epsilon\n",
" self.lr = lr\n",
" self.gamma = gamma\n",
" \n",
" def step(self, observation):\n",
" if np.random.uniform(0, 1) < self.epsilon:\n",
" return np.random.choice(self.action_space.n)\n",
" else:\n",
" return np.argmax(self.q_table[observation[0], observation[1]])\n",
" \n",
" def update(self, state, action, reward, next_state):\n",
" self.q_table[state[0], state[1], action] = self.q_table[state[0], state[1], action] + self.lr*(reward + self.gamma * np.max(self.q_table[next_state[0], next_state[1]]) - self.q_table[state[0], state[1], action])\n",
" \n",
" def set_epsilon(self, epsilon):\n",
" self.epsilon = epsilon"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Training"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype.\u001b[0m\n"
]
}
],
"source": [
"env = GridEnvironment(get_transition_func(det_state_trans))\n",
"agent = QLearningAgent(env)\n",
"episodes = 1000\n",
"delta_epsilon = agent.epsilon/episodes\n",
"\n",
"total_rewards = []\n",
"epsilons = [agent.epsilon]\n",
"\n",
"for episode in range(episodes):\n",
" obs = env.reset()\n",
" done = False\n",
" epsilons.append(agent.epsilon)\n",
" total_reward = 0\n",
"\n",
" while not done:\n",
" action = agent.step(obs)\n",
" state = obs.copy()\n",
" obs, reward, done, info = env.step(action)\n",
" total_reward += reward\n",
" next_state = obs.copy()\n",
" agent.update(state, action, reward, next_state)\n",
" \n",
" agent.set_epsilon(agent.epsilon - (5/episodes)*agent.epsilon)\n",
" total_rewards.append(total_reward)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fd1de03e320>]"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.xlabel('Episode')\n",
"plt.ylabel('$\\epsilon$')\n",
"plt.plot(epsilons)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Next, we plot total_rewards per episode. We apply a rolling mean of window $10$ to visualize easier."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fd1ddf673c8>]"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"window = 10\n",
"plt.xlabel('Episode')\n",
"plt.ylabel('Total Reward (SMA 10)')\n",
"plt.plot([np.mean(total_rewards[tr:tr+window]) for tr in range(window, len(total_rewards))])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## TensorFlow\n",
"\n",
"Next, we wish to replace our tabular representation with a neural network. We use the TensorFlow library to facilitate this. The following cells demonstrates how TensorFlow can be used to build a neural network to properly classify XOR data (a non-linearly separable problem)."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.PathCollection at 0x7fd1ddf174e0>"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# XOR\n",
"input_data = np.array([\n",
" [0, 0],\n",
" [0, 1],\n",
" [1, 0],\n",
" [1, 1]\n",
"])\n",
"\n",
"output_data = np.array([\n",
" [0],\n",
" [1],\n",
" [1],\n",
" [0]\n",
"])\n",
"\n",
"plt.scatter(input_data[:,0], input_data[:,1], c=output_data.T[0], cmap='PiYG', s=500)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"import tensorflow as tf\n",
"from tensorflow.python import keras\n",
"from tensorflow.python.keras import layers\n",
"tf.enable_eager_execution()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"class MLP(keras.Model):\n",
" def __init__(self, observation_size, action_size):\n",
" super(MLP, self).__init__()\n",
" self.observation_size = observation_size\n",
" self.action_size = action_size\n",
" \n",
" self.value_dense_1 = layers.Dense(128, activation='relu')\n",
" self.value_dense_2 = layers.Dense(128, activation='relu')\n",
" self.values = layers.Dense(self.action_size)\n",
"\n",
" def call(self, inputs):\n",
" input_tensor = tf.convert_to_tensor(inputs, dtype=tf.float32)\n",
" y = self.value_dense_1(input_tensor)\n",
" y = self.value_dense_2(y)\n",
" values = self.values(y)\n",
" return values"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"mlp = MLP(len(input_data[0]), len(output_data[0]))"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"x_range = []\n",
"y_range = []\n",
"for ix, x in enumerate(np.linspace(0, 1, 10)):\n",
" for iy, y in enumerate(np.linspace(0, 1, 10)):\n",
" x_range.append(x)\n",
" y_range.append(y)\n",
" \n",
"test_data = np.column_stack((x_range, y_range))\n",
"\n",
"plt.scatter(input_data[:,0], input_data[:,1], c=output_data.T[0], cmap='PiYG', s=500)\n",
"plt.scatter(x_range, y_range, s=100, cmap='PiYG') \n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is the results from our untrained neural network. Notice how the colors of the smaller dots (our neural network's predictions) don't match the colors of the larger dots (the actual class colors of our XOR data)."
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"pred_data = mlp(test_data).numpy().flatten()\n",
"\n",
"plt.scatter(input_data[:,0], input_data[:,1], s=500, c=output_data.T[0], cmap='PiYG')\n",
"plt.scatter(x_range, y_range, s=100, c=pred_data, cmap='PiYG') \n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following loop will train our neural network."
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"lr = 0.1\n",
"epochs = 100\n",
"losses = []\n",
"\n",
"for epoch in range(epochs):\n",
" with tf.GradientTape() as tape:\n",
" values = mlp(input_data)\n",
" loss = -tf.reduce_sum((output_data - values)**2)\n",
"\n",
" losses.append(float(loss))\n",
" grads = tape.gradient(loss, mlp.trainable_weights)\n",
" for w, g in zip(mlp.trainable_weights, grads):\n",
" w.assign_add(lr * g)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"pred_data = mlp(test_data).numpy().flatten()\n",
"\n",
"plt.scatter(input_data[:,0], input_data[:,1], s=500, c=output_data.T[0], cmap='PiYG')\n",
"plt.scatter(x_range, y_range, s=100, c=pred_data, cmap='PiYG') \n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Deep Q-Learning\n",
"\n",
"With our task setup and deep learning introduced, we can build our Deep Q-Network Agent. This class is an adaptation of our previous Q-Agent class, with extra functionality introduced to facilitate training."
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"class DQNAgent:\n",
" def __init__(self, env, epsilon=1.0, epsilon_min=0.02, lr=5e-4, gamma=0.99, memory_limit=1024):\n",
" self.env = env\n",
" self.observation_space = env.observation_space\n",
" self.action_space = env.action_space\n",
" self.epsilon = epsilon\n",
" self.epsilon_min = epsilon_min\n",
" self.lr = lr\n",
" self.gamma = gamma\n",
" self.memory = collections.deque([], memory_limit)\n",
" self.memory_limit = memory_limit\n",
" \n",
" try:\n",
" model_input_dim = self.observation_space.n\n",
" model_input_shape = (self.observation_space.n, 1)\n",
" except AttributeError as e:\n",
" model_input_dim = self.observation_space.shape[0]\n",
" model_input_shape = self.observation_space.shape\n",
" \n",
" self.model = MLP(model_input_dim, self.action_space.n)\n",
" self.model(tf.convert_to_tensor([np.random.normal(size=model_input_shape)], dtype=tf.float64))\n",
" \n",
" self.target_model = MLP(model_input_dim, self.action_space.n)\n",
" self.target_model(tf.convert_to_tensor([np.random.normal(size=model_input_shape)], dtype=tf.float64))\n",
" \n",
" def step(self, observation, verbose=False):\n",
" if np.random.uniform(0, 1) < self.epsilon:\n",
" return np.random.choice(self.action_space.n)\n",
" else:\n",
" state_tensor = tf.convert_to_tensor([observation], dtype=tf.float64)\n",
" q_vals = self.model(state_tensor)\n",
" if verbose:\n",
" print(q_vals[0])\n",
" return np.argmax(q_vals[0])\n",
" \n",
" def collect(self, state, action, reward, done, next_state):\n",
" self.memory.append((state, action, reward, done, next_state))\n",
" \n",
" def sample(self, size):\n",
" sample_index = np.random.choice(len(self.memory), size=size, replace=True)\n",
" \n",
" states = []\n",
" actions = []\n",
" rewards = []\n",
" dones = []\n",
" next_states = []\n",
" for idx in sample_index:\n",
" unit = self.memory[idx]\n",
" states.append(unit[0])\n",
" actions.append(unit[1])\n",
" rewards.append(unit[2])\n",
" dones.append(unit[3])\n",
" next_states.append(unit[4])\n",
" return np.array(states), np.array(actions), np.array(rewards), np.array(dones), np.array(next_states)\n",
" \n",
" def train(self, epochs=10, batch_size=128, verbose=False):\n",
" losses = []\n",
" for epoch in range(epochs):\n",
" states, actions, rewards, dones, next_states = self.sample(batch_size)\n",
" states = tf.convert_to_tensor(states, dtype=tf.float64)\n",
" done_masks = tf.convert_to_tensor((~dones.astype(bool)).astype(int), dtype=tf.float64)\n",
" next_states = tf.convert_to_tensor(next_states, dtype=tf.float64)\n",
" action_masks = tf.one_hot(actions, self.action_space.n, dtype=tf.float64)\n",
" target_values = tf.expand_dims( rewards + self.gamma * np.max( self.target_model( next_states ) ) * done_masks, axis = 1 )\n",
" target_values *= action_masks\n",
" with tf.GradientTape() as tape:\n",
" q_values = self.model(states) * action_masks\n",
" if verbose:\n",
" print(target_values, q_values)\n",
" loss = tf.reduce_mean((target_values - q_values)**2)\n",
"\n",
" losses.append(loss)\n",
" grads = tape.gradient(loss, self.model.trainable_variables)\n",
" optimizer = tf.train.AdamOptimizer(self.lr)\n",
" optimizer.apply_gradients(zip(grads, self.model.trainable_variables))\n",
" return np.mean(losses)\n",
" \n",
" def update_target(self):\n",
" self.target_model.set_weights(self.model.get_weights())\n",
" \n",
" def set_epsilon(self, epsilon):\n",
" self.epsilon = epsilon\n",
" if self.epsilon < self.epsilon_min:\n",
" self.epsilon = self.epsilon_min"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With our agent defined, we can train it on the environment we built."
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype.\u001b[0m\n"
]
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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HAL/84iziI8P4eI8zj2l2cQ1fnjemX6Ycj40MazNP1YNfn8+k9FieXp3jmdvqtxfOYcm0EV3dYkiwpGGMCVqHKuu4+3/OPKa//0rHeZvGpsQwIjGKAyU1PPTebg6W13Y6v1RfyUx07n3q9AxOnzmSN368mD9f0job0pR2izsNRVY9ZYwJSk3Nyrf+8YlnoN7E9DgWTkxlfU4p1fVNAExIiyU9LpI3thV45nqak5XYbzHNGp3I9vwK5mYlefadO2cUa/aVsHxjHrPH9N+zg4UlDWNMUGlqVrbmlbNi80FPwgBnhtrHrzyWhqZmzv3z+4g4I7gzElqros6endmv1UP3XDCbn507g8R2o8t/ft5Mbjt3Rp+swxHsLGkYY4LK06uzufm5jR32p8ZGICKEhoSy/IcnevZ7j7y+9+IOE2f3qZAQ6ZAwWgyHhAHWpmGMCTI5JZ0vuer9oRweGkJ4qPPxdfaRmQDMH5dM6CBdDW8wsZKGMSaoFFXWe7ZPnT6CO784i7BuksGs0Ym8/IMTGJEQ1eU5pu9Y0jDGBJUd+RWe7YnpsX4lg5mjhn4DdLCw6iljTNDYV1TF2v2lLBjnLIYUNYTWoRgqAlbSEJEs4DFgJNAMLFXVP7U7ZzHwArDH3fWcqt4xkHEaY/pXc7Ny7K/f4AdLJlNa3YAI/PmrR7HpQDnHT0oNdHimnUBWTzUCP1bVtSISD6wRkddUdUu7895T1XMCEJ8xph+9u6OQ/3t+Iw98bb4zAeALm/nC3FGMToomMzHaM5DOBBe/koY43RZmAaOAGmCzqhb15sGqmgfkudsVIrIVGA20TxrGmCHonhXbyS6u4elPsj378spqGWXJIqh1W2EoIuNF5H7gM+CPwDeA64F3ReQDEfm69EHnZBEZDxwFrOrk8EIRWS8ir4jIzC6uv0pEVovI6sLCwt6GY4wZAC1TjT+79oBnX05JjWc2WROcfLUy3Q08A0xW1VNU9WJV/YKqzgQuAEYAl/cmABGJA54FrlPV8naH1wLjVHUO8Gfg+c7uoapLVXWBqi5ITx/aM0waM9g1Nyu3vbCJ/cXOeIxKrwkJD5TWeJKJCU7dVk+p6le6OZYH/LY3DxeRcJyE8S9Vfa6TZ5R7bS8XkftFJE1Vu1+o1xgTtPLKa3n0o7aLKY1IiCS/vA7AShpBzmebhohMBs7HaW9QIBdYpqo7e/Ngt1rrYWCrqv6+i3NGAvmqqiJyDE7JqFdtKcaYwCqqrOuwb9rIBPLLnaplK2kEN19tGjcAzwHRwAZgo7v9rHusNxYBXweWiMg693WWiFwtIle751wAbBKR9cC9wMWqqr18rjEmgArKW5PGNxdNYMG4ZH5x/izPvpHWEB7UfJU0rgJmqWq9904RuQfYRC+qp1T1faDbRnRVvQ+473CfYYwJLrUNTdyzYjsA0zMT+Nm5MzzHLj12LO/tPMTE9NhAhWf84CtpNAMZQE67/RnuMWPMELf9YAVhocKk9Dg+2HWIhqZmFh+RcVj3euqTbLbnV5AeH8myaxe1OXbnF4/si3BNP/OVNK4H3hGRLUBLZ+qxwHTgB/0ZmDEmOJz+x3cB2PPrs7j0IadX/K47zyQstOdTfDy9OpsZmQm8/IMThs1U4kONr95Ty0XkVeA4nIZwwSl1rFTVxu6uNcYMfmU1DZ7tlnW4wRmEl5US06N7FVTUsjm3nFvOmmYJYxDz2XvKTQ7vt7wXkQRLGMYMD19/uHW87UVLV3q2s4ure5w08sucBvBxqdZmMZj56j11s9f2dHeqj80isltEFvR7dMaYgKmqa2SD13Kr3vYWdb5QUncKK2sByIiP9HGmCWa+KiUv9Nq+B/iJqmYBXwX+1PklxpihYOZtK7o8tjWvnMamZpqau+4BX9/Ytq9MS1fbdEsag1pPWrJGq+pLAKq6Eme8hjFmCKprbOry2LyxSWzNK+cL93/A0Xe+3uk5/1mdzdRbXyG3tMazr6DCksZQ4KtNY6KIPIfTAD5aRGJUtaVcGtG/oRljAmVnfqVn+9snTuCU6SO42G3TmJwRx9Or2/fCb+s/7vGdBZWMSorm0odW8sGuItLjI4kMC+2/wE2/85U0vuy1fR8QCiAiI4C/9VdQxpjA2pzb2pYxPTOB4ya2LoaUlexHA7jbOerlDbl8+9HV1Dc1u9daBcVg56vL7Rtd7M/H2jSMGbK25LZOOD0hzent9MI1i1Bg76GqNuc2NytvbivgZy9s4s0bFhMVHkrLbD/tSyQZ8Tav1GBnC/AaM4x9VljJaX94hyc/3k9tQxOXP/IxH+8p5mB5LWlxEdxx/kzmZiUBMCcriblZSRwzIaXNPSrqGrlt2WZyy2rJK3N6SFXVdd4mcsTI+P79hUy/C+Ryr8aYAFuzr4Qd+ZXc/NxGosNDeWdHIc2q1DU0Myk9jssWju9wzaikaO784iw255bzxKr9lHsNAKysdYZw1TQ0MSY5mmMmpLCvqJr545IJDxWuPnnSQP1qpp8cdtIQkaNU9dO+DMYYM7AKK1pnnP1gl7NMzcGyWnYWVHLajBFdXnfpseNYsfkgT6zaz3VPreOA20uqpNqZ27S6vpHFUzO464LZ/Ri9CYQeJQ0RmQpcjDNOoxaY2x9BGWP63/rsUs+MswCf7HWmCdlZ4PScOtTJuhfejspK4uSp6Z5kA61Jo6a+iegI6yU1FPls0xCRMSJyg4isAZ4Gfgico6qWMIwZxH709Lo279uP8j7otk90JSMhike/eQwzRyV49j2+0lmRr6bBksZQ5WsakXeB14F44GtuoihX1V0DEZwxpv/ERzoVDVkprd1g//LVeYxPdbrU3n3BHL/u84WjRjMywekVtXpfCbmlNTQ0KTHhljSGIl/VUxXAOCARJ3GAs+SrMWYQqqht4LUt+Zw6YwTrc8o468iRXLggi2/8/RMATpqaxtmzP9eje35j0QS+sWgCm3PLOPve9/n+k05Tp5U0hiZf4zTOFpEUnGVX7xKRsUCyiMxT1bW9ebCIZAGPASNxFnRaqqp/aneO4IwHOQuoBq7o7XONGY7Kaxt4eUMeK3cX8cK6XM/+aSMTiIts/RiIjwo/7GccMcL5XrlmXwkAkVbSGJL8mRq9GFgKLBWR0cBFwAMiMkJVx/Xi2Y3Aj1V1rYjEA2tE5DVV3eJ1zpnAFPd1LPBX96cxpgeeXZPD7S9u6bD/u4snsSO/ok+eERYawolT0nhvp9Mwnu+jTcQMTj0a3KeqB1T196p6DNCzMmzHe+W1lBpUtQLYirPQk7fzgcfUsRJIEpHM3jzXmOFon1cj90KvKUHCQ0OIjXC+O0aF936s79+vOJpnrl4IwLxxSb2+nwk+3ZY03MkKu/OlvghCRMYDRwGr2h0aTesys+CsGjgayGt3/VXAVQBjx47ti5CMGVK8u8VmJEQSExFKlFt9lBjtVEl964QJvX5OWGgIC8ansPWOM6xNY4jyVT21GNgLPAmswTMNWd8RkTjgWeA6VS1vf7iTSzo0xKvqUpwqNBYsWGAN9WZYKXXHRiTFdD7x9KYDZewsqCQ6PJSahiYWTkzlV1880nM8OTaC1beeSmps301cbQlj6PKVNEYApwOXuK9lwJOqur3bq/wkIuE4CeNfqtpZqSYHyPJ6PwbI7eQ8Y4alvYeqWPzbtwF45yeLO11KdZc7WO/xK48hOSaCCWmxHdboTouzNS6Mf7qtxFTVBlV9SVUvBRYB+4H3ReR7vX2w2zPqYWCrqv6+i9OWAZeJ4zigTFXzujjXmGHnYHlrY3NOSU2n52QXO+0ZM0clMjE9rkPCMKYnfPaecksDZ+KUNKYC9wMv9sGzFwFfBzaKSMvQ1FuAsQCq+gCwHKe77S6cLrff6IPnGjNk1NS3ziZ76UOr2Pubszuck1NSQ1pcpKcNw5je8NUQ/jAwD1gB3KWq67o7vydU9X18tJGoMyn/NX31TGOGmvLahjbvq+oaiY1s+986r7yW0Um2joXpG7762H0DmAB8B3hTRIrdV4mIFPd/eMaY7nhPSw4w87YVbWauBThYVsPIREsapm/4ShrhQCqQBqR7vVreG2MCqNxdv+K8OaM8+46+83XqGpv4+sOrWLOvmLzSWjITbZlV0zd8tWmEAw2q2gQgIpNx2jf2qmpftGsYY3qhrKaBqPAQvrFoPMvWt3YsfG/HId7beYj9xdVU1DVaScP0GV8ljRXAJAARmQR8DMwAfiwiv+rn2IwxPuSX15IWF8mRoxO54vjxjE5yShRXPra6zXmZljRMH/GVNFJUdYe7fTnwb1X9Ls7YjXP7NTJjjE/ZxdVkJccQFhrCz8+byd8uW9DmeMv0IS1TlxvTW76Shvfo6iXAawCqWoczM60xJoCyS2rarIcxKaPj4D7AqqdMn/GVNDaLyG9E5Ps4YzReBRCRRPphShFjjP9qG5oorKhjTHKMZ19kWCh3f7njutzWEG76iq+kcSVQCUwDzlDVKnf/LKCrUdzGmAHQMgLcu6QBzuyyqbERRLuD+b6/ZDIRYb2fwdYY8L0IUxXwy072fwB80F9BGWO6p6r848M9AG1KGgCTM+JZ89PPByIsMwz4WiP8eRE5U0Q6JBcRGSciPxORb/ZfeMaY8toGlm/Mo6qu0bPvg11FPL5yPwDjUmK6utSYPuerzHoN8Hlgh4h8JCLLRORVEdkF/B3YrKqP9HuUxgxjD727m+/9ay3/+HCvZ5U97+lD0uNthlozcHxVTx0Argeudwf2ZQI1wHZ3tT1jTD/blOssM3PPiu3cs2I76287jeIqZw2NEMFmrTUDyucsty1UdRfObLPGmAG0La/t2mT7iqo8a2Ssu+20QIRkhjG/k4YxZuDVNTaRV17LFcePZ1RSFL9avo3bX9zCmn0lACREhQc4QjPcWD88Y4JYXmktqjBrdCIXHT0WwJMwjAkESxrGBLHsEmcakKzkaBKiwogKb/0vOzcrKVBhmWHM1yJMn9J2KpE2VHVen0dkjPHILnYG8I1JiUFEyIiPYr+7fOvDly/o7lJj+oWvNo0L3J9XA6HAP933lwLWe8qYfpZTUk1YiHgmHEyPj2R/cTUnTU0nNc662pqB1231lKp+pqqfAcer6vWq+qn7ugHodbcNEXlERApEZFMXxxeLSJmIrHNfP+vtM40ZLF7fks/9b39GZlIUoSFOt9rEaKfh+5jxyYEMzQxj/vaeihOR41R1JYCIHAvE9cHz/wHcBzzWzTnvqeo5ffAsYwaVlzY4iyr96NSpnn3fPnEiGfGRXHrsuECFZYY5f5PGt4B/iEgUThtHLdDr6UNU9V0RGd/b+xgzFG3JK+eUaRl8ad4Yz76Fk1JZOCk1gFGZ4c5n0hCRUGCcqs4SkVQAVS3q98haLRSR9UAucIOqbu4kxquAqwDGjh07gKEZ07eWb8xDgNNmjmTPoSqWTBsR6JCMacNnl1t3ffDr3O2iAU4Ya3ES1hzgz8DznZ2kqktVdYGqLkhPTx/A8IzpW9/711q++6+1FFTU0tCkHaY9NybQ/B2nsUJErhORTBFJaHn1a2SAqparaqW7vRwIF5G0/n6uMYHw4vpcz/aNz2wAOk57bkyg+dum8R3354+99inQr3VBIjISyFdVFZFjcJLcQJZ0jBkQTc3K95/81PP+vZ2HAJiR2e/fzYzpEb+Shqpm9cfDReRJYDGQJiI5wG1AuPvMB3DGiXxXRBpxZte9WFW7HGxozGBVVtPQYd87P1ls056boOP3hIUiMg2YAXhWqFfVJ3rzcFW9xMfx+3C65BozpLVMdd5iREIkWVY1ZYKQX0lDRG7FGcw3DVgBnA68D/QqaRhjHCXVTtL466XzWDI9A4CQEFsnwwQffxvCLwI+B+Sp6teBOdi06sb0iZr6Jta6M9eOSY4hMiyUyLDQAEdlTOf8/eCvUdUmEWkUkXjgIDCxH+MyZti4Z8V2HvlgDyJOtZQxwczfpPGpiCQBjwCrgXKcMRTGmF46UFpNVko0D3xtPhkJUb4vMCaA/O091dLl9i8isgJIUFVLGsb0gZKqBkYnRTNzVGKgQzHGJ38bwh8B3sOZPNDWCTemDxVX1zMloy/m/zSm//nbEP5vYALwNxHZJSJPicg1/RiXMcNGaXU9ybERgQ7DGL/4Wz31qoi8DsyB8zBiAAAgAElEQVQDTgGuAeYDf+nH2IwZ8pqalZLqBpJjwgMdijF+8bd6agWQCHyCU011nKrmdn+VMcaXvUVVNDUr41JjAx2KMX7xt3pqB9AITAGmApNFxPoGGnMYiirr+O7jayitrmdzbjkAM0fZHFNmcPC3eur7ACKSCFyGs1Z4BmDzNhvTA399+zNe2pDL5tzyNoliUro1hJvBwd/qqauBE4GjgTyc5Vnf68e4jBlyGpqauet/2zzvf/vqDo4en0xyTDhR4TYC3AwO/g7uSwbuBz5R1XpfJxtjOtqZX9lh3yd7S5hu05+bQcSvNg1V/TXQBFwMICIpImLrqhrTA/uLqzvdn5loo8DN4OFX0nBnub0NuNXdFY3NcGtMj5TXOmtmtJ+8dqQlDTOI+Nt76gLgLKAKQFUPAFamNqYHyt2Fltbddhp7f3M2318yGYCkaBujYQYPf5NGnbtingKIiK0OY0wPldc0IAJxEU5TYnio89+vqdkWozSDh79J4zkR+QuQKCLfAF4F/t7bh4vIIyJSICKbujguInKvO3XJBhGZ19tnGhMo5bWNJESFexZXWjQ51f2ZFsiwjOkRf8dp3CUiZwL1OAsw3amqr/TB8/+Bs5zrY10cPxNnQOEU4Fjgr+5PYwadspoGEqJb/8vNH5fC5ttPJzbS1jMzg4ff/1rdJPEKeEoAF6nqU715uKq+KyLjuznlfOAxt2pspYgkiUimqub15rnGBEJRVT1J0W0nJrSEYQabbqunRCRORH4iIn8UkSVusrga+AxnZHh/Gw1ke73PcfcZM+hsyytnyggb+W0GN19fc/6J02PqI5yZbX8CxANfUdXV/RwbgHSyr0OroYhcBVwFMHasDR8xwaeoso6Cijpm2EA+M8j5ShqTVfVIABF5ADgEjFPV8n6PzJEDZHm9HwN0mF1XVZcCSwEWLFhgXVFM0MkrqwVgTLJ1PDSDm6/eUw0tG6raBOwZwIQBsAy4zK0WOw4os/YMMxgVVtQBkB5vk0Obwc1XSWOOiBS72wLEu+8FUFVN6c3DReRJYDGQJiI5OKPOw3Fu/gCwHGdQ4S6gGvhGb55nTKC0JI0MSxpmkPOVNPp1DUpVvcTHccVpSzFmUKqqa+Tqx9fw3s5DgJU0zODXbfWUqjZ19xqoIM3QsHpvMbc+vxHnu8DQt/dQFfN/+ZonYUzPTLAp0M2gZ53EzYC5aOlKmpqVzMRorvnc5ECH0++e/GQ/tQ3Nnvc/OX1qAKMxpm/4O42IMb1SUlXvmWPpnhXbh0VpIya89TvZyVPTOXp8r5oAjQkKVtIwA+JPb+xs8/7m5zbyvcWTGZs6dLugFlfVkRAVxoafnx7oUIzpM90mDREpoZPBdPRR7ykzfBRVtV3w8anV2aTERnDjGdMCFFH/O1RVT1qcNXybocVX9VQakN7Jq2W/MX7xXrXub5ct4IgR8WzOHcghPwOvqLKO1Lh+7YBozIDrtqTRvoeUiKQA3suMdRidbUx7jU3NbMsr51snTOCn58wA4MX1uazLLg1wZP2ruKqeCWmxgQ7DmD7l73KvZ4vIDpxpPVa5P9/sz8DM0HGgtIa6xmaOGBHv2ZccE+5Z/nQoKq2uZ0d+JalWPWWGGH97T90JLAK2q2oWcDrwdn8FZYaWYrc9Iy2+taomITqc8poGmofoqnUXPPAR4CRHY4YSf5NGo6oWAiEiIqr6GmCr6BmfyqobeGtbAQDJMV5JIyqcZoWq+sZAhdavdhVUAlBZOzR/PzN8+dvltkxEYoH3gcdEpABo9nGNMfzwqU95e3shACmx3iUN559eeW0j8VFD69u4d+lpileVnDFDgb8ljS8AtcB1ONVSB4Bz+ikmM4TsOVTl2U7yKmkkRjuJoqzaaddoGkLVVKU1zu906bFjufRYW9/FDC3+Jo2b3fmmGlT1YVX9PXB9fwZmBj9V9awjAZAQFea17SaNmgaeXp3NpFuWU1BeS21DEw1NzYNqxHhDUzONTc2eEkZBhfM7L5yUikhn64gZM3j5Wz11BnBLu31nd7LPGHJKqjnhrre495KjqG9s5gdLJrN4WkabD9A0d7bXQ5V1/HftAQA+99u3qap3enmfO2cUf77kqIEPvoe25pVz5p/eA+DYCSk89Z2FrWtnWM8pMwT5WiP8OyLyKXCEiKz1eu0EtgxMiGaw2XSgDIA7XnT+iUzPTGDe2OQ257R8oBZW1HmmC29JGOCM4xgMpY2Vu4s826v2FKOqtuCSGdJ8lTSeBt4Afg3c5LW/QlUL+i0qM6hVux/+hyqdD8+RiVEdzkmKCSc8VCioqKOusfNZ9vPL6zq9NphsaTeqvbCijlK3nca74d+YocLXeholqrpLVS8EooHPuy+bQsR4HCyr5Zw/v8fjK/cBravUtchMjO5wjYiQHhdJYUVdm/NPnJLG2bMzATj9j++y7WBwTzVyoLSGzMQoTp7q/JdYn1PGHS85Jayh1ivMGPB/RPg1OKWOse7raRH5Xn8GZgaPNftK2HSgnL++/RkABRV1RHstNtRVNU16fCQFFbUUVNRx1pEjufrkSdx78VFcecIEwGkkv+d/2/2Oo66xiSsfXc1f3trVi9/G/+d84S8f8OFnRcwek8gd588E4PYXN3vOCw2xRnAz9Pjbe+o7wDGqeouq3gIcC1zd24eLyBkisl1EdonITZ0cv0JECkVknfu6srfPNH0vu8SZjLClnfuzwkrGpcbw1FXHccNpU7v88EyPj/KUNMYkx3DTmdNIjo1oMwgwI8H/6ql9RdW8vjWfe1b4n2gOx6YDZby+Nd9TQqprbCYrOYa4yDBySmr69dnGBJq/SUMA74mCGtx9h01EQoG/AGcCM4BLRGRGJ6c+papz3ddDvXmmOXx1jU3c+vxGlq1vnaOypKqeG/6znt+8sg2A2oYm9hdV8/b2QmaMSuDYialcu2RKl/dMj49kd2EVdY3NbXoaJXu1BTz58f4u2zzaKyhvrea64T/rufaJtby1veumt/zyWq5/ah2XLF1JXpn/H/Yts/P+vzOdad2Lq+oJCRGOnWArBZihz1fvqZaG8n8CK0XkVhG5FfgQeLSXzz4G2KWqu1W1Hvg3cH4v72n6yZp9JTy+cj8/ePJTz77Xt+bzzJocz/tDlfX89R2naujU6SN83jMjPpL6JmdiAe8qLO/xHIBnGhJfCitbx4Q8syaHlzbk8YuXtnTZC+uVjXk89+kBPtpd5El8/th7qJqYiFBOnzmC02aM4I7zZwFwy9nT/b6HMYOVr5LGxwCqejdwFVAN1ABXq+pve/ns0UC21/scd197XxaRDSLyjIhkdXYjEblKRFaLyOrCwsJehmU6491L6E+v7+T9nYfarIdxq/uB+eTH2USGhXDmrJE+73nshBQyE6PISolm9phEz34R4bQZrUlnXXYZt72wiV+/spW7/reN+sbOZ7BpKWksmZYBQIjA7sKqTquMmpuV+976zPM+oQeN1oWVdWTERxIZFsrSyxYwNysJgAmpsRw/KZW0uAiu+dwkv+9nzGDiq8utpwpKVT8BPunDZ3dWvdX+K+GLwJOqWiciV+OUbpZ0uEh1KbAUYMGCBcHfuX8Q8k4Qf3h9B3GRYcwb54y9GJ0UzWULx/Pi+lzW55SRHh/p10jo4yen8dHNp3R6bOllC7j2ibW8tCGPB975rM2x1NgIrjxxYodr9hdXkxAVxvlzR/HJnmK+deIE/vj6TjbnlpOVEkNlXSPv7ijkrCMz2VVY6ekSDPRosaSC8loy4ju2tYSECE98+zi/72PMYOSrpJEuItd39erls3MA75LDGNot6qSqRara8j/7b8D8Xj7T9FB+eS0bckrZnFvGtJGtk+9V1jWy+UAZp07P4IOblhARFsJR7gC+2Ii+WXr+3os7HxG+bH0uZTUd1+LYnFvOjFEJnD93NBtvP53vnDSJEIEtuc5gwxueXs/3/rWWPYeqyC93qrKe/s5CIsJCqGnw3W5SVFnHqt1FrNpTbAP3zLDlK2mEAnFAfBev3vgEmCIiE0QkArgYWOZ9gohker09D9jay2eaHjrnz+9z3n0fsLOgklOnj2CU12C7oqp60r2+cV8wfwwAR41N6pNnh4RIm0Q1OskZ77Ehp4xvP7a6w/m7CiqZNjLB8z46IpRJ6XE8tTqb1XuL+d/mgwA8+uFe1u5zVg3MiI8kJiKUmnrfSePCBz/ioqUrARiT3HHsiTHDga+vhHmqekd/PFhVG0XkWmAFTnJ6RFU3i8gdwGpVXQb8QETOAxqBYuCK/ojFdK6+sdnTrVQVZo5K4Noli7nz5a380x3Il+H1jXvW6EQ2/Pw04vqopAHwwrWLqKprIjE6nBCBE+56iwOlNXy8p5jmZiXE7c5bXd9IZV0jI9p10Z06Mp6XN+R5FkUC+MeHez3b6fGRxISHekaxg9N+Ex8VRlZKTJt77S5snbH3xjOm9dnvaMxg4quk0a+jk1R1uapOVdVJqnqnu+9nbsJAVW9W1ZmqOkdVP6eq/ndxMb32/KcH2ryfnZVEVHgoC8a3ziM1LrXtB2tCVLjng7wvRIaFkhIbQWiIICJ4N5W8v+sQ5bUNVNY1ehrB21cb3fmFWV3eOzYilNjIMKIiQqmobaCgopbS6nrOuvc9vnj/h11eFx8VZgP3zLDl6yth562UZsirrGtkS57T+P3S908gJiLUUz103pxRzBubTEVtI0eMHNhFhk6ZlsGjHzmlnM8KK7nskY9JiY3g5+c5I7Iz2iUN7zU82huT7CS8mIhQVmzO54NdRZ6xF96N5O21f4Yxw0m3SUNViwcqEBM8quoamXXbCs/7WaMT2xwXkQ5VNwPl1nNmcPnx4zn73vfZkV8BOIPrWsaPjErq2KspLERobFb+eNFc5o1N5unV2dz31i5PqSQm3PlvUFnXyE+f3+S5TlU77QV2ih9jUIwZqvwdEW6GkWCeJDA8NISJ6XGMS43hyY9bh/mkx0fy2DePYXJGx5JPy7iNRZPTGJsaw4S0WKA1wcREhrY5f0am05heWde6vreqEhMRyryxSdx4+hF9+0sZM4j0XYulGTJ++O91gQ7Bp99eOId12aX87tXtlFQ3MDYlhpOmdj758h8vnsu6/aWeksVZR2aiwElT0wBIaVeFdelxY/m//25qs355TkkN1fVNfHn+GMJC7buWGb4saZg2ahuayC1tHUH9v+tODGA0XZs1OpFZoxOdmXBXbO8w9Yi3mIgwjp+c5nkfHRHq6R4MMLpd99mWJFJe0+Bpx9nsjvWYOaptVZ0xw40lDdPGzvxKmr3G1HuPewhGLQsdxfVi7YprPjeZjPhIZo9JorKu0dNlsGUxJXAGDoa2GzdizHBkScO0caDUmeb81186ksTo4F9E6JTpGXxz0QS+cvQY3yd3ISo8lK8vHO95n13s/Bl8VljJwkmplNc28Oc3dzF1RBxR4aFd3MWY4cGSxjBW29DETc9u4IenTiU2MpTbX9zCdPeb9CnTMzqdXynYZMRH8bNzO5tR//CNSY4mISqMW5/f1KZL8fGT0rq5ypjhwZJGLzQ3K7f8dyMVtY38apB8M/f22pZ8nl+XS2OzMjEtlpc35PHyhjxCBFJjh+9YBBHh+0umcOfyrby9vYD/bXKmH/nKgk4nWTZmWLFuIL2QX1HLvz/J5uWNeXy6vyTQ4fRYy4p7r27JZ9vBCs/+1LjIYT/i+dsnTSQ5JpzdhVV85k4fkpEwfBOpMS0safRCZW1rP/6WOZoGk5Z1Juobm3l1S75nv/cqesNZYnQ4H+0u8rxv3zXXmOHIkkYveA/+KhiESaOlwbc9+0btSIgO9/Sgmjc2qU/n1DJmsLKk0QveSWMwljQOdLKiHVhJo4X3an5Pf2dhACMxJnhY0ugF7+qpnJLOv7UHs7yy2jbvf+HOCGslDUdLx4bo8FAbBW6My/4n9EKFW9KYPy65zXKog0F9Y3OH1erOmz2K5JhwZmTaqGdonWbdn1X9jBkurMttL7SUNI6dkML9b39GcVW9Z4RysCuvderqbz9vJl8/bhwKhIYIq2/9/LDvOdXi5rOmtVmwyRhjJY1eKa6qJ0Tg2ImpQOv8RINByxrbidHOokkticISRqvIMGf0d8v8U8YYK2n0yta8ciamxzFnjFOdszm3nBOndD7Tqi+1DU2EiBARNjB5vNwraZiurb/tNMIskRrjEdCShoicISLbRWSXiNzUyfFIEXnKPb5KRMYPfJRd25xbzqxRCSTFRDA6KbpX7Rqzb3+V8//yQR9G171yt2otIdq+N3QnMTqc2Ej7MzKmRcCShoiEAn8BzgRmAJeISPtJhL4FlKjqZOAPwF0DG2XXiirrOFhe65kqe8aoBLblHV7SaGxqpr6xma2Hef3hyHd7TllJwxjTE4EsaRwD7FLV3apaD/wbOL/dOecDj7rbzwCnSGfrbw6QP72+k/E3vcz4m17mzW0FAMwc5UwdnpkYRWE360p3Z8+hKp/nXPvEWj7327cP6/6deXVLPqMSo5iQFtdn9zTGDH2BLHePBrK93ucAx3Z1jqo2ikgZkAoc8j5JRK4CrgIYO3Zsf8XLH17f4dletj4XcEoYAEkxEZTVNNDUrD1uTM71Gi/R3Kydjjx+aUPe4YTMRQ9+xKo9xcwbm8Rz31vk2b+vqIrZY5Ks4dsY0yOBTBqdfVrpYZyDqi4FlgIsWLCgw/H+sC67lNFJ0SS58xGlxISj6vRK6mm324Ly1qRRVFXvGR/QF1btKQZg7f5Szr73PWaOSiAtLpKCijoWTkrts+cYY4aHQCaNHMB7rukxQG4X5+SISBiQCBQPTHht1TW2HeBVUdvIwomtH7rJbqI4nLEa3tVaOwsquk0ajU3Nhz06eXNueZvGepsuxBjTU4Fs0/gEmCIiE0QkArgYWNbunGXA5e72BcCbqjogJYn2WuaW+vHnp3r2ea8XneyWOK59Yi1fuv8Dnli1n4fe2823/vEJNfXdjyguKG9NGr94aWu355Z7TV2y/WAFlyxdyXs7Cz376hub+fHT69mZX9Eh0bVn04UYY3oqYCUNt43iWmAFEAo8oqqbReQOYLWqLgMeBv4pIrtwShgXByrelqQxOaO14fjs2Zme7TlZSZwxcyRV9Y1sO1jBYx/t9axR8Wl2SbervpVW15OVEk1lbSPbDpajqni393vnyXKv6q9XNuXx0e4iUmIjPONDPtpdxLNrczhUWcdvL5zT7e+UlRLj529vjDGOgHZAV9XlwPJ2+37mtV0LXDjQcVXXN/KnN3Zy7ecm886OQmIjw6hvbAZgTHLrB613AkmMDueBr88H4J4V2/jLW595jm3JLe82aZTVNJAYHc7lC8fzy5e3Ul7TSGKM0xX2nR2F3P2/bZ5zy2sb2Huoinvf3Mlzaw8ATpVWi/3udOcpsRGeqUK6MtPmmDLG9JCNWurEE6v28+A7u4mLCON3rzk9pm45axrgrB996bFjOWZCSpfXeycToNNBf89/eoCD5bVcffIkymsbSYwOJ81tYzhUVedJGpc/8nGb67KLa9h+MN+TMAA+K6yitqGJqPBQtrjPigoP9UwV8rsL5/Dkx/upqm9ia145EWEhnDFzpOcZxhjjL0sanXhmTQ4Az67N8ex7/tNcRiVGkRwbwZ1fPLLb6zPiozzb6fGRHeakUlWue2odABfMH0N5TQMZ8XGkxjnVTocq6kiPj+Tv7+/1XHPjGUfw+1d38KvlWz3nAcREhFJd38S2gxXMzUpii/us0up6SqvrAZiYHssz3z2+p38MxhjTgU1Y2E5ZdYOnLWJvUesaGTsLKvj8jBF+3cO799OJk9PYXVhFc7Oyq6CCjTllnmVWwWkraameailpFFXVs3xDXptxIefOHkVcVBgHSmvYkFPGMeNTiIsM87RbtCSmlvWsS6rrPQ3sfdmF1xgzvFlJo52WdoDPzxjBa+662XdfMJuvLMjq7rI2Mrw+pKdnJvDcpwcorWng1N+/C8ADX5vnOV5QUUd5bQMJXklj28EKnlndOu5xybSMDo3Wp87I4OmrF6KqJESF8eTH+zlpSrpnNcHc0lpP470lDWNMX7GSRjstH7oT02I9+9q3UfiSGB1OfFQYo5OiyUxyqqoKKloH8HmP7n5zaz61Dc0kxYSTHBOOCNz7xs42o8Rbus5es3iyZ98xE5wxIiLCtJEJbDpQzol3vwXAhLRY9hdXs/tQFYnR4Z4pvo0xprespNGOJ2mktyaNeWOTe3QPEeHjW05FBDbkONVG3muIv7Qhj2kj49l2sIJHP9oHOGs2hIWGkBITQVFVPRGhITxyxdF87eFV1DU4PbeuPHEClx8/npr6pjaN2NERbZPCyVPT2XOoire3FzAyIQpjjOkrVtJop2U1vvGpTtL40rzRh3Wf6IhQosJDSXMbrb3X4/7KgjE8893juWD+GM++luqnlkburJRoJriJ6+SpzhgMcdfb8NXr6cxZIwEoqW5gWmb8YcVvjDGdsZKGq6lZOVBSQ3aJ0/idGhfBx7ec4pke5HAluFOP3/jMBs++s47MJC4yjGkjWz/Qx7lJIy0ukh35lcRFhTM6KZpVt5zic7oP73l/RyZEcezEVNLiIjlUWeeZhdcYY/qClTRchRV1nHTPWzz03h4A4iLDyUiIIvww53lqEdduAZ9pI+NZfEQGAPFRzrEpGXGkuomh5We8e92IhKhOZ731Nnt06yC9L7olo5Zk4T3ViTHG9JaVNFwtPZ5aRlS3fKD3VmRYCOGhQkOTMxWI98jwhCinFHLR0a09s1qqs9onm+784JQpnHxEBqDMHpMEwOwxiby3s5AZmVbSMMb0HUsaLu9v83dfMLvPlvgUEeIiwyipdrry/uT0IzzHzpg1kocuW8CSaRmefS3dbkND/V/nIiw0hPnj2jbWX3nCRI6flNbr6jVjjPFmSaMTPRmT4Y+WhDElI65NTycR4dR2AwZb2i8ielktlhgTbutlGGP6nCUNLy9eewKlNfX9dv+dBZU+zzlt5ghySqdw/txR/RaHMcYcLksaXo4cE/hG46SYCK73WrPDGGOCifWeGgB/u2wBx0xI4bnv2aSBxpjBzUoaA+DzM0b4PdmhMcYEMytpGGOM8VtAkoaIpIjIayKy0/3Z6eROItIkIuvcV/v1w40xxgywQJU0bgLeUNUpwBvu+87UqOpc93XewIVnjDGmM4FKGucDj7rbjwJfCFAcxhhjeiBQSWOEquYBuD8zujgvSkRWi8hKEekysYjIVe55qwsLC/sjXmOMMfRj7ykReR0Y2cmh/+vBbcaqaq6ITATeFJGNqvpZ+5NUdSmwFGDBggV6WAEbY4zxqd+Shqqe2tUxEckXkUxVzRORTKCgi3vkuj93i8jbwFFAh6RhjDFmYASqemoZcLm7fTnwQvsTRCRZRCLd7TRgEbBlwCI0xhjTgagOfG2OiKQCTwNjgf3AhapaLCILgKtV9UoROR54EGjGSW5/VNWH/bh3IbCvF+GlAYd6cX1/C/b4wGLsC8EeHwR/jMEeHwRXjONUNd3XSQFJGsFMRFar6oJAx9GVYI8PLMa+EOzxQfDHGOzxweCIsT0bEW6MMcZvljSMMcb4zZJGR0sDHYAPwR4fWIx9Idjjg+CPMdjjg8ERYxvWpmGMMcZvVtIwxhjjN0saxhhj/GZJwyUiZ4jIdhHZJSJdzbo7EHE8IiIFIrLJa1+nU8mL41435g0iMm8A4ssSkbdEZKuIbBaRHwZhjFEi8rGIrHdjvN3dP0FEVrkxPiUiEe7+SPf9Lvf4+P6O0X1uqIh8KiIvBWl8e0Vko7s0wWp3X9D8PbvPTRKRZ0Rkm/tvcmGwxCgiR0jr0g7rRKRcRK4LlvgOm6oO+xcQijM9yUQgAlgPzAhQLCcB84BNXvvuBm5yt28C7nK3zwJeAQQ4Dlg1APFlAvPc7XhgBzAjyGIUIM7dDgdWuc9+GrjY3f8A8F13+3vAA+72xcBTA/R3fT3wBPCS+z7Y4tsLpLXbFzR/z+5zHwWudLcjgKRgi9F9dihwEBgXjPH16HcJdADB8AIWAiu83t8M3BzAeMa3SxrbgUx3OxPY7m4/CFzS2XkDGOsLwOeDNUYgBlgLHIsz8jas/d85sAJY6G6HuedJP8c1BmctmSXAS+4HRdDE5z6rs6QRNH/PQAKwp/2fRTDF6PWs04APgjW+nrysesoxGsj2ep/j7gsWXU0lH9C43WqSo3C+yQdVjG7VzzqcyTBfwylJlqpqYydxeGJ0j5cBqf0c4h+BG3GmycF9XjDFB6DAqyKyRkSucvcF09/zRKAQ+LtbzfeQiMQGWYwtLgaedLeDMT6/WdJwSCf7BkNf5IDFLSJxwLPAdapa3t2pnezr9xhVtUlV5+J8oz8GmN5NHAMao4icAxSo6hrv3d3EEKi/50WqOg84E7hGRE7q5txAxBiGU5X7V1U9Cqii61VAIUB/jm7b1HnAf3yd2sm+oPscsqThyAGyvN6PAXIDFEtn8sWZQh5pO5V8QOIWkXCchPEvVX0uGGNsoaqlwNs4dcRJItKyHIB3HJ4Y3eOJQHE/hrUIOE9E9gL/xqmi+mMQxQe0WZqgAPgvTvINpr/nHCBHVVe575/BSSLBFCM4SXetqua774Mtvh6xpOH4BJji9l6JwClKLgtwTN66mkp+GXCZ2+viOKCspdjbX0REgIeBrar6+yCNMV1EktztaOBUYCvwFnBBFzG2xH4B8Ka6lcr9QVVvVtUxqjoe59/am6p6abDEByAisSIS37KNUye/iSD6e1bVg0C2iBzh7joFZ/mEoInRdQmtVVMtcQRTfD0T6EaVYHnh9FzYgVP3/X8BjONJIA9owPnm8S2c+us3gJ3uzxT3XAH+4sa8EVgwAPGdgFNk3gCsc19nBVmMs4FP3Rg3AT9z908EPgZ24VQVRLr7o9z3u9zjEwfw73sxrb2ngiY+N5b17mtzy/+JYPp7dp87F1jt/l0/DyQHU5ktOQEAAAI9SURBVIw4HTGKgESvfUET3+G8bBoRY4wxfrPqKWOMMX6zpGGMMcZvljSMMcb4zZKGMcYYv1nSMMYY4zdLGsb4ICJN7WYr7XYWZBG5WkQu64Pn7hWRtN7ex5i+ZF1ujfFBRCpVNS4Az92L01f/0EA/25iuWEnDmMPklgTuEmftjo9FZLK7/+cicoO7/QMR2eKuj/Bvd1+KiDzv7lspIrPd/aki8qo7+d6DeM1FJCJfc5+xTkQeFJHQAPzKxljSMMYP0e2qpy7yOlauqscA9+HMH9XeTcBRqjobuNrddzvwqbvvFuAxd/9twPvqTL63DBgLICLTgYtwJhCcCzQBl/btr2iMf8J8n2LMsFfjflh35kmvn3/o5PgG4F8i8jzONBfgTMXyZQBVfdMtYSTiLMD1JXf/yyJS4p5/CjAf+MSZ+otoWie5M2ZAWdIwpne0i+0WZ+Mkg/OAn4rITLqfAruzewjwqKre3JtAjekLVj1lTO9c5PXzI+8DIhICZKnqWzgLLiUBccC7uNVLIrIYOKTOmiTe+8/EmXwPnEntLhCRDPdYioiM68ffyZguWUnDGN+i3VUAW/xPVVu63UaKyCqcL2CXtLsuFHjcrXoS4A+qWioiP8dZbW4DUE3rNNm3A0+KyFrgHWA/gKpuEZFbcVbRC8GZAfkaYF9f/6LG+GJdbo05TNYl1gxHVj1ljDHGb1bSMMYY4zcraRhjjPGbJQ1jzP9vrw4EAAAAAAT5W68wQEkEmzQA2KQBwCYNALYAfEd7ilYupOUAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Parallel Training Complete.\n"
]
}
],
"source": [
"env = GridEnvironment(get_transition_func(det_state_trans), normalize=True)\n",
"agent = DQNAgent(env, lr=0.001, gamma=0.5)\n",
"\n",
"episodes = 1000\n",
"training_batch_size = 32\n",
"epochs = 10\n",
"delta_epsilon = agent.epsilon/episodes\n",
"\n",
"episode = 0\n",
"def train_agent():\n",
" train_step = 0\n",
" while episode < episodes - 1:\n",
" if len(agent.memory) >= training_batch_size:\n",
" train_step += 1\n",
" agent.train(epochs, training_batch_size)\n",
" if train_step % 50 == 0:\n",
" agent.update_target()\n",
" print('Parallel Training Complete.')\n",
"\n",
"try:\n",
" p1.join()\n",
"except:\n",
" pass\n",
"p1 = threading.Thread(target=train_agent)\n",
"p1.start()\n",
"\n",
"total_rewards = []\n",
"epsilons = [agent.epsilon]\n",
"\n",
"step = 0\n",
"for episode in range(episodes):\n",
" obs = env.reset()\n",
" done = False\n",
" epsilons.append(agent.epsilon)\n",
" total_reward = 0\n",
" last_target_update = 0\n",
"\n",
" #print(f'Episode: {episode}')\n",
" while not done:\n",
" action = agent.step(obs)\n",
" state = obs.copy()\n",
" obs, reward, done, info = env.step(action)\n",
" total_reward += reward\n",
" next_state = obs.copy()\n",
" agent.collect(state, action, reward, done, next_state)\n",
" step += 1\n",
" \n",
" if episode % (episodes//5) == 0 and episode > 0:\n",
" window = 50\n",
" plt.title('Episode {}'.format(episode))\n",
" plt.xlabel('Episode')\n",
" plt.ylabel('Total Reward (SMA {})'.format(window))\n",
" plt.plot([np.mean(total_rewards[tr:tr+window]) for tr in range(len(total_rewards)-window)])\n",
" plt.show()\n",
" \n",
" agent.set_epsilon(agent.epsilon - delta_epsilon)\n",
" total_rewards.append(total_reward)\n",
" \n",
"window = 10\n",
"plt.title('Final')\n",
"plt.xlabel('Episode')\n",
"plt.ylabel('Total Reward (SMA {})'.format(window))\n",
"plt.plot([np.mean(total_rewards[tr:tr+window]) for tr in range(len(total_rewards)-window)])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype.\u001b[0m\n"
]
},
{
"data": {
"image/png": 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uQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"tf.Tensor([ 0.63407003 -0.65647415 1.00743481 -0.63589331], shape=(4,), dtype=float64)\n"
]
},
{
"data": {
"image/png": 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XOUEWQQAAAABJRU5ErkJggg==\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"tf.Tensor([ 0.99954647 -0.79179145 0.86502867 -0.84954549], shape=(4,), dtype=float64)\n"
]
},
{
"data": {
"image/png": 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,
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"tf.Tensor([ 0.80478743 -0.97439052 1.06423397 -0.9485818 ], shape=(4,), dtype=float64)\n"
]
},
{
"data": {
"image/png": 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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"tf.Tensor([ 1.1005514 -1.15272373 0.90672973 -1.14455366], shape=(4,), dtype=float64)\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"env = GridEnvironment(get_transition_func(det_state_trans), normalize=True)\n",
"#agent = DQNAgent(env)\n",
"\n",
"obs = env.reset()\n",
"done = False\n",
"agent.epsilon = 0\n",
"env.render()\n",
"plt.show()\n",
"\n",
"while not done:\n",
" action = agent.step(obs, verbose=True)\n",
" obs, reward, done, info = env.step(action)\n",
" env.render()\n",
" plt.show()\n",
" \n",
"# 0 - down\n",
"# 1 - up\n",
"# 2 - right\n",
"# 3 - left"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Apply DQN to OpenAI Gym Environments"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[33mWARN: gym.spaces.Box autodetected dtype as <class 'numpy.float32'>. Please provide explicit dtype.\u001b[0m\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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+xLkXnzyLf7+6Lee4l23ax8u7u44o37q/N5KhxdnIlESWAz929yOeLTP7wFgvHk5Y/BIww93bzWwKcA9wLNAHfNDd14bnbgQ6CRJa3N1z/0uJSFb2dPXTVFdDfQkOLR1JXU01E6qrhobGJm1o7+b1J8xgyftfRV3N6H6n2mqjusro6I2zZV8vAP/2/rahYbf/9MiLbN6bdhPYrLg7V9/z9LBNcBcePz3nxy6kTEnkOmD3MMfOG8uFzWw+cAmwOaX4FmClu19uZicBdwEXpRx/o7u3j+W6IhJYvWU/z+/oHPGcVVv2l11TVlJTfQ1dsUObs7Yf6OO1x00fdQKBYAveSfU1dPQNkHCnttq4+OSZQ2uK/eqZ7Ty4envO8Xb3J+iKxfmrNxzLVYtajzg+t0R3acw0xHfdCMe2jvHadwA3E+ySmHQK8IXw8Z8zswVmNsvdd47xWiJymOu/s4ztBzIPsHzjiTOKEE3+Hb6Sb0ffAF2xOHMn576h1qSGWjp6B4gNDDJl4oRDFqWc2VzP/p4BYvFETkkq2f90zIymkt635XCRdPeb2WXAVndfddjKoKuAKwg2vVoEHE2wk+JOgsUfHzIzB77h7kuKHLZIxUgMOjs7+vjA+Qu49oKFI547c1J5jcxKaqyrOaQ5a/v+IGGO5RN9c30NHX1xqixxRD/RzObgedrdGRsaDjwa7V3lOZy6YEnEzB4GZqc5dCtBs9WlaY7dBtxpZisJFntcASQ/SrzW3beZ2UzgN2b2nLs/Nsy1FxOs+0Vr65HVQpHxbl9PP4MedBqX06fe0WiuO7Q5a9v+oB9jTkvuSWRSfVATSbgf8WafTLa7ckwiyZpIuQ2nzjmJmNnZ7r5iuOPufvEwP3c6sBBI1kLmAcvNbJG77wCuCc8zYEN4w923hV93mdn9wCIgbRIJaylLANra2jynX1CkgiX3Ip9eRrsVjlZTfQ27Og821207ECSRMTVn1dfycnsXsfgg86ZMPuTYzObgcXd1xHJ67HKd2DmqJGJmJwBXEuxs2AecNdoLuvsaggUck4+5EWgLR2dNBnrCVYOvAx5z9w4zawSq3L0zvH8p8LejvbaIBNo7w0mEZfaGNRqNdTV07T7YJ7J9fx/VVTb0Zp+LSQ01dPTG6Y7FmTZcc1ZXjklkaImZ8vqbZLMp1TyCxHEVUA3MB84t0KZUJwP3mlkCWAdcG5bPAu4Pay41wPfd/VcFuL6MM09v2Mu3n9gY9LiVkD87r5Xzjy3ckM6hmkhzBddEDusT2Xagl1nNdVSPYRHDSfW17O3upz8xeEQSmdo4ATPY3ZHbalDtXf0015ffcOpMM9YfI6g1/BB4n7s/a2Yb8plA3H1Byv0ngOPTnPMycGa+rikC0DeQ4CP3raB3IMGMEnoz3by3B8eLk0QquDmr+bAhvtv39zFnjMNkJzXUDs1Sn3pYLa6muoppjXXs6sy9Oasc/x6ZaiKdBCOkWoDkrjQl9plNJDff+v1GdnT08cPF53HuMdOiDmfIB775NJv39hT0Gu1d/UyormJSfWmux5QPTXU19A0MEk8MUlNdxfYDvZx2VMuYHjP1+Tq8JgJBk1auSaS9M5b2MUtdpnkibzezqcC7gdvNrBWYYmbnpJvFLlLK9vf0c/13ltEZzh14ub2LN544o6QSCEDr1Iks27QPd8eyXJpjtJIbTRXq8UtBcnfD7liCSQ3GtgN9XHpqugGj2ZvUcHBdrHTL48+cVHdIZ/5o7OmOlezSJiPJuP6Vu+919yXu/kbgdcDfAV83s00Fj04kjx59fjdPbdjLtKYJzJ3cwCWnzOZzl50WdVhHaJ06kc6+OAcKuG9Fe1eMaWXYdDIazWES6YwNsKe7n/74IHNbcu9UBw7ZjCpdB/jM5rrcR2d19Zfl32RUddlwlvpXgK+Y2TGFCUmkMH7/UjstDbV8+5pFJblDXFJrOG9j894eJk8sTPNGe1eMGWX4hjUayZV8r77n6aGyfPSJJKVvzqqnvStGYtBH1YGfGHT29vQzvdKas8zspxl+/oo8xiJSUE+8vIdzF04t6QQC0DrtYBI5Y97kDGfnpr2zn5NnTyrIY5eKVy+Yyh+dOZfe/mCE1qlzWzh34dQxPWZyOfjqKqOl4cgl32dOqmPQg6ap0Qwl3tfTjzsVWRN5A7ARuA9YRrCPiEjZeWVvD6/s7eXa1468xEcpmB/Odt60pzCd6+7Onu5YRQ/vBZjRXMc/X3V2Xh8z2Zw1ZWJt2g8jybkiX3noBaY2TqCpvob3v2YBTXUjv9UObf5VgUlkFvBmgjkiVwEPAPe5+/OFDkwkn554eQ8AryngsNl8aayrYXpTHa8UaIRWR2+cgYSX5RtW1JLNWcNNCDxlTgstDbX8ZPkWAAYSzq6OGJ+97NQRH7dcN/+CzKOzBoAHgQfNrIEgkTxuZp9x968VI0CR0fjyr5/nv5/bdUT5rs4+pjVO4IRZ5bEhZ+vUhoIN8909NEek/N6wotY4oZoqGz6JtE6byKrPHFwW8BM/Wc33ntrEtRcsHHGNsvbu8l1BIJsZ67XAWwkSyAnA14D/LHBcIjn52cqtDA46p8w9dD7A3MkNXJSy90Opa506kaWb9hXksZMTDSu9Y70QzIzm+lqmZblI4scuPoH7V2zlL+5dyrEzhv8AsynczCrbxy0lmTrW7wbOAX4N3O7uK4sSlUiOOnoHuOKceRmbD0pd69SJPLBqG0++vIeqPCe+P2zYC5RnJ24peM+r53N6lpMWZ7fU89nLTuXuxzfw/M6RNwC7+OSZaTvrS12mmsg1QAdwPbA45VOcAe7uYxvqIJJHg4NOZyxeEbOwj5vVzKDDlUueLMjjV1cZsyeNbc7EeHXL204e1flXLWpNu1Nhpcj0aiu/tCjjVld/HPdDx/KXq7edNps5N7yG/vhgQR5/elMdLRPL/3mS6GWTRAbcPQFgZscR9I9sdHf1i0hJ6QhneKfOKi5XNdVVvHqBKvpS+jIte/Jr4FgAMzsWeJpgH/T/Y2b/UODYREalozdYEys5IUxECi9TEpnq7i+E968GfuDuf0kwd+SPChqZyCh19FVOTUSkXGRKIqnLvr8J+A2Au8eAwjTWiuRoqDmrAvpERMpFpnr/M2Z2G7CVYI7IQwBm1oKWQJES0xEu8a6aiEjxZKqJXAd0AScBb3H37rD8NILVfEVKxsGaiPpERIol07In3cDfpyn/HfC7QgUlkotkn0imxe5EJH9GrImY2c/M7K1mdsSr0syONrNPm9kHCxeeSPY6euM01dVQU51xrzURyZNMr7YbgUuAF8zsCTN7wMweMrP1wDeBZ9z9nlwvbmY3mZmb2fTw+ylmdr+ZrTazp83stJRzJ5vZj83sOTN71sxek+t1pTJ19A1UxGx1kXKSqTlrK/Bx4OPhRMM5QC/wvLuPvBBMBmY2nyBBbU4pvgVY6e6Xm9lJwF3AReGxO4Ffufu7zWwCMPySmDIudfQOaGSWSJFlXe939/Xu/lt3XzrWBBK6A7iZQ4cRnwI8El7vOWCBmc0ys0kE+7vfHR7rd/f9eYhBKkhQE1ESESmmSBqPzewyYKu7rzrs0CrCLXfNbBFwNDAPOAbYDXzTzFaY2b+bWeMIj7/YzJaa2dLdu3cX5peQktPRG9fILJEiK1gSMbOHzWxtmts7gVuBT6f5sduAKWa2EvgwsAKIEzS7nQP8q7ufDXQDnxju2u6+xN3b3L1txowZ+f7VpESpJiJSfAX72ObuF6crN7PTgYXAqnBp+XnAcjNb5O47CJafx4KDG8LbRGCLuz8VPsyPGSGJyPikPhGR4su0KdUKDu2zOIS7nzPaC7r7GmBmyjU2Am3u3m5mk4Eed+8nmOj4mLt3AB1m9oqZnRju734RsG6015bKVUl7iYiUk0yvuHeHX28AqoHvhN//GZCPzvXDnQzca2YJgiRxbcqxDwPfC0dmvUxYYxGBytpLRKScZBri+xKAmZ3v7q9NObTCzH4HfG6sAbj7gpT7TwDHD3PeSqBtrNeTylRJe4mIlJNsO9abzOy85Ddmdi4w/K7zIkXW2ae9RESikO0r7lrgW2ZWT9BH0gdouRMpGaqJiEQjYxIxs2rgaHc/zcymAbj7noJHJuNOR98Az27ryOlnl23eB6hPRKTYMiYRd0+Y2ceAnyh5SCHd8tM1PLh6+5geY0ZzXZ6iEZFsZNuc9eswkfyQYKIfAOHwW5Exc3ee2rCXN5w4g8UXHpPTY0yeOIFZk+rzHJmIjCTbJHJ9+PX/pJQ50JrfcGS82rKvl92dMS46aSbnHzc96nBEJEtZJRF3n1/oQGR8Wx72aZzdOiXiSERkNLIeDxkuzX4KMNRe4O7fL0RQMv6s2LyfiROqOWl2c9ShiMgoZJVEzOxTwKUEe63/Gngz8DigJCJ5sXzzPs6Y16JdCUXKTLY1kfcAZwHL3f3PzWwO8I3ChSWVLjHo/GLNdnrC5UrWbetg8ety61AXkehkm0R6w6G+cTNrBnYQ7PEhkpNlm/bx4ftWHFJ2wfHqUBcpN9kmkRXhCrv3AEuBDmB5waKSirevpx+Ab17zak6c1UxdTRXTmjTHQ6TcZDs6KznE9y4z+zUwyd2VRCRn3bFgrauF0xqZO7kh4mhEJFfZdqzfA/wW+K27ry9sSDIedIVJpEn7f4iUtWyHwvyAYDfCfzOz9Wb2QzO7sYBxSYVLrrrbVKckIlLOsm3OesjMHibY5/wi4EbgVcBdBYxNKlhXLE5ttVFXoyG9IuUs2+asXwMtwB8ImrXOc/dthQxMKlt3LE5jXQ1mFnUoIjIG2X4MfAGIE+w6eAJwnJlpKI3krKsvrqYskQqQbXPWhwHMrAV4P8Fe6zMBDauRnHTGlEREKkFWNREzu8HMvkfQnPVu4F7gnWO9uJndZGZuZtPD76eY2f1mttrMnjaz08LyE81sZcqtI1yaXspUt5KISEXI9lU8Bfga8Ad378/Hhc1sPnAJsDml+BZgpbtfHi74eBdwkbs/T7DsSnKnxa3A/fmIQ6LRFYsztXFC1GGIyBhlVRNx9y8ACeBKADObamZj3UvkDuBmgn1Jkk4BHgmv+RywwMxmHfZzFwEvufumMV5fIqQ+EZHKkG1z1qeAzwCfCosaGMMKvmZ2GbDV3VcddmgVcEV4ziLgaGDeYedcCdyX67WlNHTG4jRroqFI2cv2Vfxu4GzC9bLcfauZTRrpB8J5JbPTHLqVoNnq0jTHbgPuNLOVwBpgBcGosORjTgAuAz6Z4dqLgcUAra3afLEUdcfiNE5QEhEpd9m+imPu7mbmAGY2MdMPuPvF6crN7HSC2e+rwjkC84DlZrbI3XcA14TnGbAhvCW9lWA5+p0Zrr0EWALQ1tbmI50rxZcYdHr6E1ryRKQCZPsq/qmZ3QW0mNk1wLXAN3O5oLuvIRgeDICZbQTa3L09XCm4J+y8vw54zN07Un78KtSUVfaG1s1Sn4hI2ct2nsjtZvZWoB84E/i8u/+yAPGcDNxrZglgHUGyAoZqP5cA1w/zs1ImupVERCpG1q/iMGn8EoKmJjN7j7v/cKwBuPuClPtPEMyKT3deDzBtrNeT6GkFX5HKMeLoLDNrMrO/MbOvmtmbwuRxA/ASwcx1kVHTCr4ilSPTq/g7QDfwBMHKvX8DNAN/6u5LCxybVKhkTURDfEXKX6ZX8XHufjqAmX0daAeOPqyzW2RUkn0ijaqJiJS9TJMNB5J33D0BbFACkbHqUnOWSMXI9Co+08z2hvcNaA6/N8DdfWpBo5OK1JlszqqrjTgSERmrTElEK+RJ3h1szqqOOBIRGasRk0jYhCWSV12xOPW1VdRUa2tckXKnV7EUXWdfnCY1ZYlUBCURKboureArUjGURKToumNx9YeIVIgRPw6a2T4O3TRq6BAanSWjcPuvnuN/ntsFwOa9PZx+VEvEEYlIPmRqU5helCik4v1izXb644OcMa+Fo6dN5LIzj4o6JBHJg1GNzjKzqUB9StG2QgQlladvIMHrT5jBF999ZtShiEgeZbs97tvN7AVgC/BU+PW/CxmYVJZYfJD6WvWDiFSabDvWPw+8Fnje3ecDbwYeLVRQUnn6BhJKIiIVKNskEnf33UCVmZm7/wY4p4BxSQVxd/oGBqmr0WDFHxomAAAOtElEQVRAkUqT7WD9A2bWCDxOsPPgLmCwcGFJJelPBP8qqomIVJ5sPxr+MdAHfIygGWsr8I4CxSQVpm8gSCKqiYhUnmxf1Z9094S7D7j73e7+FeDjhQxMKkdsIBjkV6eaiEjFyTaJvCVN2dvzGYhUrlg8bM5STUSk4mTaY/16M1sBnGhmy1NuLwLrxnpxM7vJzNzMpoffTzGz+81stZk9bWanpZz712b2jJmtNbP7zKx++EeWUtIX1kTUJyJSeTJ1rP8IeAT4AvCJlPJOd981lgub2XzgEmBzSvEtwEp3v9zMTgLuAi4ys6OAjwCnuHuvmf0IuBL41lhikOJI9okoiYhUnhFrIu6+z93Xu/ufAA0Eb/qXADPycO07gJs5dG2uUwiSFu7+HLDAzGaFx2qABjOrASai2fJlIxYP+0TUnCVScbKdsX4jQa2kNbz9yMz+KteLmtllwFZ3X3XYoVXAFeE5i4CjgXnuvhX4MkGtZTtwwN0fGuHxF5vZUjNbunv37lzDlDxRTUSkcmU7T+R6YJG7dwGY2T8Avwe+NtwPmNnDwOw0h24laLa6NM2x24A7zWwlsAZYAcTNbArwTmAhsB/4DzN7n7t/N9213X0JsASgra0t3SrEUkQH+0RUExGpNNkmEQMGUr4fCMuG5e4Xp30gs9MJksEqMwOYByw3s0XuvgO4JjzPgA3h7c3AhnDWPGb2U+B8IG0SkdKSHJ1VV6OaiEilybSfSI27x4HvAE+a2U/CQ5cD387lgu6+BpiZco2NQJu7t5vZZKDH3fuB64DH3L3DzDYD55nZRKAXuAhYmsv1pfhUExGpXJlqIk8D57j7F83sf4ALCWogN7j7HwoQz8kEy6okCIYQXwvg7k+Z2Y+B5UCcoJlrSQGuLwXQF9cQX5FKlSmJDDVZhUkj74nD3Rek3H8COH6Y8z4DfCbf15fCi2nZE5GKlSmJzDCzYZc3CZc/ERmRaiIilStTEqkGmsjQiS4yEi3AKFK5MiWR7e7+t0WJRCpWLJ5gQk0V4Wg8EakgmT4a6lUvYxYbGNTiiyIVKtMr+6KiRCEVTVvjilSuTGtn7S1WIFK5YvFBJRGRCqU2Bim4voGEOtVFKpRe2VJwas4SqVxKIlJwQXOW/tVEKpFe2VJwQXOWaiIilUhJRAqub0A1EZFKpVe2FFwsnqBOfSIiFUlJRAqub2BQo7NEKpRe2VJwsbhGZ4lUKiURKbhg2RMlEZFKpCQiBdcXT1CnjnWRiqRXthRUYtAZSLhqIiIVSklECioW1/7qIpVMr2wpqOSGVOpYF6lMkSYRM7vJzNzMpoffTzGz+81stZk9bWanpZz7UTNba2bPmNnHootaRqNvIKiJaIivSGWK7JVtZvOBS4DNKcW3ACvd/Qzg/cCd4bmnAX8BLALOBN5hZscXN2LJRSyumohIJYvy4+EdwM2Ap5SdAjwC4O7PAQvMbBZwMvCku/e4exz4X+DyIscrOUjWRNQnIlKZInllm9llwFZ3X3XYoVXAFeE5i4CjgXnAWuB1ZjbNzCYCbwPmFzFkydHB5izVREQqUU2hHtjMHgZmpzl0K0Gz1aVpjt0G3GlmK4E1wAog7u7PmtntwG+ALoJkEx/h2ouBxQCtra1j+TVkjJLNWZonIlKZCpZE3P3idOVmdjqwEFhlZhDUNJab2SJ33wFcE55nwIbwhrvfDdwdHvsHYMsI114CLAFoa2vz4c6TwjvYnKWaiEglKlgSGY67rwFmJr83s41Am7u3m9lkoMfd+4HrgMfcvSM8b6a77zKzVoImr9cUO3YZveQQX43OEqlMRU8iGZwM3GtmCWAdcG3KsZ+Y2TRgALjR3fdFEaAcanDQ+fJDz/Pirq60x3d29AGqiYhUqsiTiLsvSLn/BJB26K67X1ismCR7D6zaxtcefYljZzQyYZjO8wuOm85RkxuKHJmIFEPkSUTKV398kH/8zfOcPGcS//XhC6iqsqhDEpEiUxLJweCgs+KVfUPt/ZVgd2eMB1Zt45W9PVn/TF88wSt7e/nWNacpgYiMU0oiOXj0hV188FtLow4j7+a01HPW/MnYKPLBVYtaef0JMwoXlIiUNCWRHLy4M+hEvveDiyqmw7i+topT57ZQrRqFiIyCkkgONu/tYfLEWl6nT+AiMs5p8H4ONu/toXXqxKjDEBGJnJJIDl7Z28N8JRERESWR0YonBtmyr1c1ERERlERGbfuBPuKDztFKIiIiSiKjlZxHoZqIiIiSyKhtDpOI+kRERJRERm3T3h5qqow5LfVRhyIiEjklkVHavLeHo6Y0UFOtp05ERJMNh/FH//z40IZKqbbs66VtwZQIIhIRKT1KIsM4dkYj/YkjF1g8flYTf/Iqbe8uIgJKIsP66pVnRx2CiEjJU8O+iIjkTElERERypiQiIiI5UxIREZGcRZJEzOyzZrbVzFaGt7elHPukma03s+fN7M0p5W8Jy9ab2SeiiFtERA4V5eisO9z9y6kFZnYKcCVwKjAXeNjMTggP3wVcAmwB/mBmD7j7umIGLCIihyq1Ib7vBH7g7jFgg5mtBxaFx9a7+8sAZvaD8FwlERGRCEXZJ/IhM1ttZveYWXIK+FHAKynnbAnLhisXEZEIFawmYmYPA7PTHLoV+Ffg7wAPv/4j8EHA0pzvpE92PsK1FwOLw2+7zOz57CM/xHSgPcefLSTFNXqlGpviGh3FNXq5xHZ0ticWLIm4+8XZnGdm/wY8GH67BUhdU2QesC28P1x5umsvAZZkHezwsS1197axPk6+Ka7RK9XYFNfoKK7RK3RsUY3OmpPy7eXA2vD+A8CVZlZnZguB44GngT8Ax5vZQjObQND5/kAxYxYRkSNF1bH+RTM7i6BJaiNwPYC7P2NmPyLoMI8DN7p7AsDMPgT8GqgG7nH3Z6IIXEREDookibj7n49w7PPA59OU/wL4RSHjSmPMTWIForhGr1RjU1yjo7hGr6Cxmfuw/dMiIiIj0rInIiKSMyWRNEpliRUzm29m/2Nmz5rZM2b20bB82GVjihzfRjNbE8awNCybama/MbMXw69F3QbSzE5MeV5WmlmHmX0siucsnAO1y8zWppSlfX4s8E/h/9xqMzsngti+ZGbPhde/38wmh+ULzKw35bn7epHjGvUySUWK64cpMW00s5VheTGfr+HeI4r3f+buuqXcCDruXwKOASYAq4BTIoplDnBOeL8ZeAE4BfgscFMJPFcbgemHlX0R+ER4/xPA7RH/LXcQjHkv+nMGvA44B1ib6fkB3gb8kmCu1HnAUxHEdilQE96/PSW2BannRRBX2r9d+FpYBdQBC8PXbXWx4jrs+D8Cn47g+RruPaJo/2eqiRxpEeESK+7eDySXWCk6d9/u7svD+53As5T+TP13At8O738b+OMIY7kIeMndN0VxcXd/DNh7WPFwz887gXs98CQw+bCh8AWPzd0fcvd4+O2TBPOximqY52w4Q8skufsGIHWZpKLFZWYG/ClwXyGuPZIR3iOK9n+mJHKkklxixcwWAGcDT4VF6ZaNKTYHHjKzZRasEgAwy923Q/APDsyMKDYI5hOlvrBL4Tkb7vkptf+7DxJ8Yk1aaGYrzOx/zezCCOIZzTJJxXYhsNPdX0wpK/rzddh7RNH+z5REjjTc0iuRMbMm4CfAx9y9g2DZmGOBs4DtBFXpKLzW3c8B3grcaGaviyiOI1gwKfUy4D/ColJ5zoZTMv93ZnYrwTyt74VF24FWdz8b+DjwfTObVMSQhvvblcpzdhWHflgp+vOV5j1i2FPTlI3pOVMSOdJIS68UnZnVEvxzfM/dfwrg7jvdPeHug8C/UaAqfCbuvi38ugu4P4xjZ7J6HH7dFUVsBIltubvvDGMsieeM4Z+fkvi/M7OrgXcAf+ZhI3rYXLQnvL+MoO/hhOEfJb9G+NtF/pyZWQ1wBfDDZFmxn6907xEU8f9MSeRIJbPEStjWejfwrLt/JaV8uGVjihlbo5k1J+8TdMquJXiurg5Puxr4ebFjCx3y6bAUnrPQcM/PA8D7w9Ez5wEHks0RxWJmbwH+L3CZu/eklM8ws+rw/jEEyxG9XMS4RrtMUjFdDDzn7luSBcV8voZ7j6CY/2fFGEFQbjeCEQwvEHyCuDXCOC4gqGquBlaGt7cB3wHWhOUPAHMiiO0YgpExq4Bnks8TMA14BHgx/Do1gtgmAnuAlpSyoj9nBElsOzBA8Anw2uGeH4JmhrvC/7k1QFsEsa0naC9P/q99PTz3XeHfeBWwHPijIsc17N+OYFXwl4DngbcWM66w/FvADYedW8zna7j3iKL9n2nGuoiI5EzNWSIikjMlERERyZmSiIiI5ExJREREcqYkIiIiOVMSERkFM0vYoasEj7jKs5ndYGbvz8N1N5rZ9LE+jki+aYivyCiYWZe7N0Vw3Y0EY/rbi31tkZGoJiKSB2FN4XYzezq8HReWf9bMbgrvf8TM1oULCf4gLJtqZj8Ly540szPC8mlm9lC4iN83SFnzyMzeF15jpZl9Izk7WiQKSiIio9NwWHPWe1KOdbj7IuBfgK+m+dlPAGe7+xnADWHZ54AVYdktwL1h+WeAxz1YxO8BoBXAzE4G3kOw+OVZQAL4s/z+iiLZq4k6AJEy0xu+eadzX8rXO9IcXw18z8x+BvwsLLuAYJkM3P2/wxpIC8EmSFeE5f9lZvvC8y8CXgX8IVg2iQaiW+RSRElEJI98mPtJbydIDpcB/8/MTmXkpbnTPYYB33b3T44lUJF8UXOWSP68J+XrE6kHzKwKmO/u/wPcDEwGmoDHCJujzOwNQLsH+0Gklr8VSG7E9AjwbjObGR6bamZHF/B3EhmRaiIio9NgZitTvv+VuyeH+daZ2VMEH86uOuznqoHvhk1VBtzh7vvN7LPAN81sNdDDweW7PwfcZ2bLgf8FNgO4+zoz+xTBjpJVBKvK3ghEsgWwiIb4iuSBhuDKeKXmLBERyZlqIiIikjPVREREJGdKIiIikjMlERERyZmSiIiI5ExJREREcqYkIiIiOfv/NEKMg3GkRvAAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Training Stopped\n"
]
}
],
"source": [
"import multiprocessing as mp\n",
"\n",
"env = gym.envs.make('Acrobot-v1')\n",
"agent_a = DQNAgent(env)\n",
" \n",
"episodes = 1000\n",
"training_batch_size = 32\n",
"epochs = 1\n",
"delta_epsilon = agent_a.epsilon/episodes\n",
"\n",
"manager = mp.Manager()\n",
"shared = manager.Value('episode', 0)\n",
"def train_agent(shared):\n",
" train_step = 0\n",
" while shared.get() < episodes - 1:\n",
" if len(agent_a.memory) >= training_batch_size:\n",
" train_step += 1\n",
" agent_a.train(epochs, training_batch_size)\n",
" if train_step % 50 == 0:\n",
" agent_a.update_target()\n",
" print('Training Stopped')\n",
" \n",
"p2 = mp.Process(target=train_agent, args=(shared, ))\n",
"p2.start()\n",
"\n",
"total_rewards_a = []\n",
"epsilons_a = [agent_a.epsilon]\n",
"\n",
"step = 0\n",
"for episode in range(episodes):\n",
" obs = env.reset()\n",
" done = False\n",
" epsilons_a.append(agent_a.epsilon)\n",
" total_reward = 0\n",
" last_target_update = 0\n",
"\n",
" #print(f'Episode: {episode}')\n",
" while not done:\n",
" action = agent_a.step(obs)\n",
" state = obs.copy()\n",
" obs, reward, done, info = env.step(action)\n",
" total_reward += reward\n",
" next_state = obs.copy()\n",
" agent_a.collect(state, action, reward, done, next_state)\n",
" step += 1\n",
" \n",
" shared.set(episode)\n",
" \n",
" if episode % (episodes//10) == 0 and episode > 0:\n",
" window = 100\n",
" plt.xlabel('Episode')\n",
" plt.ylabel('Total Reward (SMA {})'.format(window))\n",
" plt.plot([np.mean(total_rewards_a[tr:tr+window]) for tr in range(len(total_rewards_a)-window)])\n",
" plt.show()\n",
" \n",
" agent_a.set_epsilon(agent_a.epsilon - delta_epsilon)\n",
" total_rewards_a.append(total_reward)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[<matplotlib.lines.Line2D at 0x7fd18c137cc0>]"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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qxIRVqJz7PQWOP7+CYzEYBgwZyX4z5csP4KHPnYiDxw2p+HWqGX3z3Kod+MkTK3Hz+2ZhwrBBRR37zIrt+J97XivqmGxMDSRpiSz/fCYs2QdSnAmrt4YmLNXEF0cIiHuxQyYsq88y0QvlgcwDsBZu1duFML5BgyEWmWz4H/rF1buqIkCqabq449m1eG7VTizZ2Fa0APnx40GgZtwRikkwaUVP+qLZVD4tL8cHUoRM6PGc6OWEEcdFfHdNDRZ6Mk6s7zJIzmTM2X84jp82Ciu2tddnGC+AsQCuh5sw+D0AJwLYwMyPM/Pj1R6cwdBfySjLy3L6W0RR3fBNry5VCSWFDxxTfDVduYpu1FwqTFhX/3Wx71SWEc2ZLHId7qVoIOls9QWIMGFdMW9a6H30Me5vmxkzxw/B50+b0ac9TwpFYWWY+Z/M/GEAx8Nt/vQsEV1Rk9EZDAOFKnllq2m6ELkQpUymQ5oC40bcCCGhUTQkrMhj5Ha3ciKewNdASqjGK4Tl65v2+g7raiGEfzIRHRQgI+7FcdgPJujLnidxMtEbvP4dd8AtM3IrgH9Ue2AGQ39m9v7DQ++rpYFUc+IQE3XGdrClrQeb9nTHPraxIVH09cTk2JCwsKMjjV8+s1orSCxp1tL1TmfJB0JFTq6yWWxzEfdbCuJSDd4NxdEmxTEOB9FofdnzpFAm+q8AvATgOADfYeYjmfkGZn4r6jiDwRDGqpIGUk0fSMKTemmbccy3H8dxNz0R+9hUIrjf2Jnokg8EAG584E1tgcGEJI11j1VoZaKUCRBfC7Il30emjIKOcXCcsAZy53/WFDxGPCOH2c+HsYjqNoz3Eri9Oy4D8AQR7fJ+dhORqYZrMORBNS1VK/pEXnku29KOXz6zumLnFpNzt8bPUAj59outxtuQCKYlXYFBWeuwNKqduJyIwpLPXQhZA6n2pKzer8j1iIKZsa29B11pOzBhFZnrUkkKRWGV3pjYYNiHUU0KtdBAzvnxs0jbDj5xwtSK1HISY27rzhTYM3pccfjH4k34zJ9eBuBGJQl0Zd1loaHTLGQfiNBW4g4nVFK+ypFYgcku/nflMDD3m278Evk+kDo1YcETIMxsM7MNVxu5AsC7vPcGg0FDzrxXNR9IcKG05wCuVBKjmHw7e4v/Vy+2tMYtjy73X7c0ButaXQSYrIHoLhP2gbjb4k6wssCqtgYixpSw4udzf+ehpf7r/mDCehjAgQBARAfC9YfMBPAFIvpWlcdmMPRb1Am0aiYszSK5nGZMOnoyxQuQcF2rwuORFabmVOCA102Msg9Ed+5wOXd337jyLFtDH4iQjcVoIE8s3ea/lk1Y9RqFNYKZxdLgIgB/ZuZPATgDwDlVHZnB0I+pmQlLuo64RKWS4MTk3ZWnbHr0se7vC46cGGt1LGsVg0MaSLQJS3duv5QJBdFvcfNl7Br6QMTfSFLSQIq5piWZsOq1mKI8qncCeBQAmLkXwABsVW8wVAZ1IqhWcb6HlmzxX/thtxVKghOTbncJGggzo6nBwn5Dm2JN3rKAbU7FN2Hp5lvHFyCBBhLbhNXHPpDOIgIW5DyQvuoHUsiJ/joR3QRgI4AZAB4BACIaClPWxGDIizqxVWsxK9vE3QmFK+YDEf05Nu4uPh/C9hLdRDVcx2FtxJRAFrAtjYEJq1cjDOUoLb0TXZiwgkmWY8oC22EkLULW4ZppIKGos4wDNMU7XvaB9FUtrEIayCcBdAA4GMCZzNzpbT8UwC3lXtxrlctENMp7/2EietX7eY6IZkn7nklEy4hoJRF9udxrGwzVRP2HrsU/uLCEVKIMR0/G9lfgb2zeW/TxDruagtAWCq2QZQ2kRdJAdP6XpLRi153XL+eOIA+kGCd6k5cEKcxnSza24cll26IOKwmhXBXy6eSDJA2kozeLZ1fsqOj44hCpgXgC40bN9v8A+E85FyaiSQBOg1seRbAGwDuYeTcRnQXgNgBHE1ECwE+9/TcAmE9E9zPzG+WMwWCoFupEUAsTQ6Eig3HpSmcx8/qHyzqHw+z240gEeRhRyelyINKgVLQGImsdOitTyAdiFWfCsh3X9NbRG5ghz/7xswCAtTe9O9Y54iIWFbIGUowAEYLHrfcFfORXL+KZa07GpBHNFR1nFIUy0e8lorOIKEfQENH+RHQ9EX28xGv/AMA1kPwszPwcM+/23r4AYKL3ei6Alcy8mpnTAP4M4LwSr2swVB11Dq9FfxAxWWZLKH4o094T2OFlh3YxuJnSkgZS4P5lDURekf/ymdU5vc/lOVYfhRWck2JqQIKs46AxmfBfVxOdD6Q4J7r4HRwvf3e1oJAJ60q4q/7lRPQ8Ed1PRI8Q0UoAvwbwOjPfUexFvdpaG5l5ccRunwDwL+/1BABy+ZQN3jaDoS7J6TZXpgC58z9rMOXLD6AzosCfmDzSZQoQeejDmkvLJZZ9IEDhCVxM9FNGNoeE79It7Xh+ddg04xQUIIEPRAiwYrLhG5PutKiGQ//z1U3xThKToJii7NOJf7wQHESlmcAqQSET1kYAVwG4ioimAdgPQDeAZczcHnUsET0GYJzmo2sBfAXA6RHHngxXgJwgNumGl+fYSwFcCgCTJ0+OGqLBUDUcZhw2YSjeefAY/PDxFWU7ZO/4z1oAwI6O3lCinY5K5oEMb05hQwlOdIddp7mfCV5QA/F+W4T2nnDme1rprSJPkrrTBi1tS/CBOIyUJ0DU7+zavy/B2YePj3WeQuzs6MW1f18CIKj9pbtmFH4xRUkNqHUwVuwUSGZeyczPMPOCQsLD2/9UZj5U/QGwGm5G+2IiWgvXTLWIiMYBABEdDuCXAM5j5p3e6TYAmCSdfiIA7XLA698+h5nnjB49Ou7tGQwVxXaAsUOa8MkTp3rvy/vPFpOMbArLF/ufth2s2dGp/SwOP396lf+6ZBOW4znRNePWIYekqhV21ck/5APROdGRa94pppSJcKKrY65kKPb6XUGRSNkHUoyvTDxbq141kGrAzK8BGCPee0JkDjPvIKLJAO4B8FEpgREA5gOYTkRT4YYUXwjgQ7UbtcFQHOxVS00WUao7Ct8U5ESvvgHgfT9/HgDw6OdPwvSxrUVf687n1vqvk0VkScvYzKFihoU0kIQvQHJNCznmQNmEpTmvwyyZd/LvpyMrmbBsxQdSrbwF+RkXkxCo84HUWoDEL8JSG64HMBLArUT0ChEtAABmzgL4NNzSKm8CuIuZX++7YRoM0YhJTEQXlauBCAEiJ9YVcvJu2dtT9HXUiTZhEaaOain+PJ4JKxnbB+L+1jWAUp8dI1qIOhw+nxhPHGyH/V4mahb87q4MHnh1c6zzFEL2WzSEMtHjn8PSaCC1zgapuQaiwsxTpNefhJt7otvvQQAP1mhYBkNZ+E7kIsuJ5yOZyD1PoXNSCWtmtQxK0iIMKqU5lCMEqIgMi2/CUoWYOvfHcaKT7x8ozoTVlc5KGkjuQVf+cRHefXhlw3mTJUdhBVqboNYlTSIFCBG9jAihxsyzKz4ig2EAwIyQE7l8DcSd1MIaSDzHdDGoq26LKJSXEReH3ck7acXTAPw+5lautqI+u5ATXetFD+69mGq8W9p6sHVvry92axF6DYQFSJxxtqQS6EzbgdkvlIhY+fFFUUgDucD7fTmABIDfee8/DKCgI91g2FcRPgARCVSuAGnwJgk5sa6gXb8UAaIk7iUThOElhPLaIpEwphNdPB9df29VoITzQHLPJftAgmq8hZ//tnbX5DdnynA88sbWqvoT5K+mVB+GaqYDalPxQCbSB8LMq5h5FYDjmPkqZn7Z+7kaEWG4BsO+jsPsrxATVvnF7vz2stn4Gkgp4bxq8cKEZeHb5x8OwF35xoW9+4/rRM/KAiTHhFVcFJbDwQQddCQsPGYhxKaOGqy9brUIC5D4xwVRWMG2WmsgcZ3og4noGPGGiI4GMLg6QzIY+j+Og5AdvtyVoTBzyAJETHhv22+I9phSamJlVCc6AaNbG4vucih8QHGd6IEGoikDo9yGPER9LazcHIk4K/ugxWx8oVMJhg1qwPHTRobGEIXYw1L8PHGPryRxBcgnAPzSK2S4Am6ehtbZbTAYhBnFfZ0gKtueLnwgaY0P5OLj9sd/efkmMqVkpKsmLHHdYs1wtuPa5uM60cXnCYs0AiO/DyRfNV4h64TQK06AWLGPqQSWRbj8HQcWfU3xbGXBXu3yKzljKLSDV8hwfy8J8GgAxzDzYcw8v+qjMxj6KaIWFOD+o1cqkbA3I2kg3qSbtCxMG5NrEChJA7Fzo7AA0fUu/j2IPJhEzAl81qRhAIBb3n9EjlDITSSUPtMWU+ScENc4QxffUcIiENU2oikR09QHhItFuscGn9WdBuL1Pv+c93qnlB1uMBjyYEsmrGSRk68OMRHKK0zxOpkgHDi6MgJE1VrkibiYe7A9R7aoxrt6e3RmPBEwanAKk0Y0FxWFpTNhhX0gucdEjRlwvy/hzC92Qn59Uxs6IuqVCdSzFlv0EYA2CqtWkWOCuCash4noc0S0HxENET9VHZnB0I8RK3DAXdGq/9hrdnTiew8vi73KFeeSw2zlFfN+wwblHNNbiglLMTUlJUdtxmYsXLcr1irZ8fwQk73S4ks2tkXuz1LuRqFmXPIj0z0/Rm4UlnhWK7d1hLo4yviOfMuLnGPWdkTMx5odnXj3j57FNXdH1Yh1UQVaUDOs8HVEyLN4XiETVpX7uKvEFSCXAfgCgJcAvO79LKnWoAyG/o4cSqpzon/8zvn4yZMrsaktXra4r4FIE9rKbR3u+YnQrEn2K6W1bW4UFvnXAID3/ux5vLC6sBHCTSQEDhw9GIMaEgXrSInaWeJY9Vyh9wWKKbqZ6OHVudjv1FuexuW/X6gdQ2ASdMvAO8xF+ZF2dvQCAOav3V1gT13Gvxh7ERqI8t0AtfeBxMpEZ+ZJhfcyGAwCEYUE6J3oosdF3GQ/cS5ZQ/jMn14GAGxr79Um+5XiRFd7byQ0jto4JhrZB5SwcnM7dPvnMzdF1cLSmZhYOpf4HUfTE+Yj0ceEuTghvKMjDQBIJQqvy9VhR5mwcsOY3d/qPQJ16AMRENHBRHQ+EX1I/FRzYAZDf0YOJbU0GojfsyJmtp+Yv+VSI0dNGQEAOHL/4X75DZlSfCB/f3lj6H1SEgKCOHOU7bBkYik8sclag7rvim0doUm0YB6Io6uFFW/MgHuvFrlaghDCwskfhdBsUprvIt+1BEHfEn1YsuCLZxzkv/b9U9J3U4zJrRLEEiBE9FW47WV/DuAsAP+HIEvdYDAo2NIqOKlJJBTzB8csf+dndEsayIFjWjCiJYVDJwzV5miUIkAalOq7umS1OKt5NZGy0DFu5FRwrMzdCzdg2dZ2aV9oX/vbkFuNN87KXOwjO9EzXi+SYrLxdcI8Z4zKwKMSHsXz+MJpM3DlydNy8kDkRMS/zH9LPbyqxNVAPgDgZACbmfmjAGahDgoxGgz1ihrGq5qwxARSrNNT9oH0ZpzIyaoUE5YqdHQmrDiRQqIWFqAvT5K7fzDpX3xcbk5LW1cmtK8/Fm0599zJNZYJS8qGJy+hUTzDYYPiC5BYGogqQCKqNndlPHOnYu+US+ALWptK6yBZKnEFSLcXzpslolYAWwAcUL1hGQz9G9kkk9CU5xCTYDFlxoFwpnjazi9AUkmroAayYXcXnli6Fau3d/jb1CisRFkmLPe1RYVLuciT/gnTR2HtTeGKt3bIbBVsX7g+12EtJxIWU4030EAsz2/D/jMc1pwqfAKPUnwgYpy6RmDPLHdb+vraoZoHEgrjrUMTFoCXiWgYgDsALIAbjbWoaqMyGPo5IgoJENnVehNW3Lh9x9dYVA1EX5+qKWkV1EA+/ceX8fE7F+Cjv3opOKcidBxlsgLireZZ1sBiJOXJk772c29YWdvBsq17fZPSFk0UG7PsAwnOHz5f7nh8DcQK8l6ET+GYA0ZEjl8mjgaijkcIz+88tDRn3860G7Rw1qH7hY/RZaLXYxgvM1/GzHuY+acA3g3gMmb+WHWHZjD0X9QopHzJcHFrZPkaiDRB9Gbt0GT1sw8H3RWaGhIFNRDRe1xMUO75w8ds9SboYivG2hzOxSjkg5CDDvKdDwB++PgKLNm4F7ue06szAAAgAElEQVS7MjhswtA8TmfZB6LPhNdpREEioeWF8QbPo6UxiY8fPxWtES1+i+mbon7vUfcuhHpjQ3i6FsccNmGov60uEwmJ6A4iuoSIpnm90Y32YTDkgZnDJiyNE52L1EDEvC6bKHqzYRPWWYcFK9RBqcICRAgjeXLPd4wsqOK4VhwnXOyvmDBe/fncE+zsTPvbLIugW3DrfCC6Lodt3ZlQSHI2pIEAa7Z3Yt1Ot3d5Q8JCwor+vka0pPxzFyKfCUtHr+cDaVIElLCUTRnZHLqHNzbtxZ6uNGpBXBPWnwFMBXC7V1DxL0R0ZRXHZTD0W8RcFSrnnkcDiRu3H5iwZA3EyVmVChpj+ECEOUxeDasaiBB8584anzOWQuOVmzoVOkZ2ogu+e8HhOdeUNY5EHtNY1nFChSyB3Axvhxmz/vcRHPOtx4Ntig/k+dU78YW/ulnlqaSFhGVFfl9CuBcT8SWIEp6+BuIJ8ehMdAfv+tEzOOcnzxYcQyWIa8J6BMDXAHwRwO0AjgXw+eoNy2Dov4jJTp7EyhUgYj/h12jrzmDhut15fSCpGD4Q4ZCXtaO07WDeQaOD95IT+b4rjwcQnrQ7erPY3NatHW8okbCIPBDB++cE+cvi/sXvVMLKaxpr78n60Uj5OhKK43QaiNzHRJBKWNpw7PA5w+eJQhV8+f4Only2DZ29WRDlOud1Zi9xnrd25X4n1SCuCethAM8BuAjAGrgVeaeVe3EiupqImIhGKduPIiKbiC6Qtl1ERCu8n4vKvbbBUC1e37QXQBB+qdNAijVhqRrIvV7C35jWRu3+qUQxGkiwLZ11QhOVfI6xQ5q8sQT7X/Cz53Dst5/QjjfU57zAbXIhE5YvcIHxQ5uw7MYz81Y53tuTRWtT0r824AoVWYjpgpVsb2MiQTkOfdeE5V4vX0BAMZF1qiDqUioAAMDTy7fjkl/Px61PrUJj0vIFrKrhytQ6kTBuLsdyAG8HMB3AVgBbiGgnM/eWemEimgTgNADrle0JAN8B8LC0bQSAGwDMgRvEtpCI7mfmwkVnDIYac9O/3EiaF72aUQmLcibzYsN4fQHiTXLdnnC64ZxDtPs3xBAgvg9E0UBkf0dvNpjYxAQvT9pLt+g7WzssV/ItnDsi+y10iHnRYfYmePJKxOTeY3tPBhOHu8UlRX7FF/66GMulZETdceIaIpFQJpW0/Ofihk/nan7iucSJhFLl3gGjW3L22dEeTK+q/wOANmpNjaKrNnFNWJ9h5hPgJhS2we2NvqfMa/8AwDXIrWz8GQB/A7BN2nYGgEeZeZcnNB4FcGaZ1zcYqkKzV5dKrCp1TnQxeccNuxT7+7+9iULNHBckE4XLr4vVqupElzUQeaILVsDxfCBiaBYVzkQv5ES3JZNflG+pO21jb3cWQxQNBAAeeG1zzvlC1/CEikWU49RuSJD/XPIJZtXMFoX6PJpTSZx16DhMl/q6yAJCl++jc7z3ZHI1mWoSSwMhossBnAjgKACbAfwWwDOlXpSIzgWwkZkXy3ZPIpoA4P8BeKd3LcEEAHKO/gZvm+7clwK4FAAmT55c6hAN/Zh7Fm3AyMGNeMeM0YV3rgKDvclruJd8pvoA9vbos6qj6PJCbcV5MrYDovzRO3GS97Ihk46bh9HZm0WTVJjxW+cf5r+OSsqTy7ED4WKSbp/zyKFofSChzyV/jVwDSpa/G3Z34YTvPAkAGNyYK0Bcv0i3d77cawgNRDSUkkklJA2kgACJk8z30ydX5mxLJqzQdxIWIImc7TqNTS2GWW3imrCGA7gVwHxmjhUfRkSPARin+ehaAF8BcLrms/8D8CVmtpU/Jt1flva/g5lvg1u3C3PmzKltULShLrjqLjdyRs1mrhUinPOHFx4BILcab4/0Tx7XB9LR4woQIRQyDqPBsvJOupYm+13GcRi2w0h6ZVZsZuxsT2N3VwYzpFXwBKnPSFRzJtWsw7IJq4Dz2d2/gAbi3YsjayAUjiCTs7iTiaAVr0BoJYBeA0nbtluJN48JS7S6VbP11XMW+ko7e7NYvrUjZ3uDFTbJyWNISjdy5cnTcOdzazF2SK7/q7seNRBm/jYRHQPgQgC/9XwSg5l5fcQxp+q2E9FhcEOChfYxEcAiIpoL18fxZ2/7KADvIqIsXI1jnnSaiQCeijN2w75F3MS8amE7jCUb2zBuSBPGeE5n1dkr26njjrej1/bPD7gmrHzmK6Bw7oWo6tvUkEBHbxa2w9iy100anCzlFcjka/gEuKtyWYDYTrikerxM9MKJhKEaYxQ20+3oCHwGSWkfQassQDRCQK4tpgqzhhgaiCNpIMyMW59ahSP3H45jDhipvRcAuOwdQUWohEV5TZpyHazPnToDnzt1hn4MNf7zL6Ya7w0AvuptGgTgj6VckJlfY+YxzDyFmafAFQ6zmXkLM0+Vtt8N4ApmvheuQ/10IhpORMPhai8P57uGYd+l1pm4Kt9/ZBnmr93tayGAV41X1kAyxWsgnV64qZhgsg77q2yZe644Dt8+/zDXcR2Vs+CdR0yYctmOVCKBX198FH75sTmhY3wNRHNeXZBAVCa+bjw6c9z33jcrdE25VbAsmJ9atg2/fyFYz+oq1coyTF7pC3NSb9bxndXRTnT9Kl98l7btCuObH16GT/5mQc5+svC6+Lgp/utkwgppN7JA1UVc1QNxTVgXwI3CWgQAzLyxli1tmXkXEX0DwHxv09eZeVetrm/oP9S6oY7Kdi9y5kcffLu/TV0pyxqIHcNebjvsmybE6jVtO75JRWb25OGYPXk4nly6LdK/ogoQ2+GQY/6E6WNyjgl8IHoTloysUYiyIIXuUZcUeeJ0N8I/rIF445Ge6+3PrMarG4K4Hl8DkU4p53xskyKcVnjRWT0Z238eqjaUtAInui7SSRaqWYf956trvpXJY6ZqSFDo70EegVqJt16Im4ney64OygBARHodtwQ8jWOHZvvFzHy39P4OZp7m/fy6Utc3DCxqXY009/qMSSMGYZrkR7AUc5IcGhsnbF+2a8smrFSECUsVWipiEmv0VtyOEwiBhjzFAKOaM4m+GfI4Q76KGA79hJV7Xf+aUoSTLgrLdhhvnzwc75090T1OY8KSa36Jbo5AIBBkDUQWCKmE62tKJd1z6Xwg4WrBHHm/8iJHllOqCUsee6ECv49+/qRQAmitiCtA7iGinwIYSkSXAHgEgJnEDXVHrauRqmRsBw3KRJhQzEm9mUBqxBF4cgXeTXu68aHbX8COjl6tCcu/ZgGzkTBX+RoIB6tmdfyCfFndQK5Zx2G1H0j09yIc+rr7EJ+La8vOeXGLbh5JoHnofCAiEAEINEUgECCyBiJ/L8J0lUq4wkXnA5GfdcbmWOZDABgi9e9oSFiKdhIcU8iENX1sa6ioYq2I60T/DhGdBSANt5nUN5n5X1UdmcFQAn3tA8nanGNaUp3oPdlcjSLynNI+m9t6sNmrkHugJvlMvqY4bOG63fjYr14EA/jNx+fiqCkj9CYsXwPJH9kF6H0gOWXgHakfiJU/jJeZsWp7BzK2o/WBiIlTzLmqZiNHZyWTlm+y0nVSzOf8FhqhW1vMFRKyiUsEK0Q50cMCxIk2H3r7/uADs0IJgqrQl2VGHBNWMo/gryaxr8jM/2LmzzPz5wA8REQfqOK4DIaSKNUHsnxre0ktYFUytoOk2hZW9YFIGkicsMt8WpXOByKwJLPRym3t6Ezb6ErbfqirX1NKcqL7Jqw8501EmLDUBDa5pW1UJvp9r2zCqbf8G0u3tGs1EL/NrWSqCmsganRWYN4Cwr4MedzDmoNaWeL7kDWQdklbEc8jyoku7q+pwUJv1on0+Qg/hzrhN1iEjC2XSgnGHpWlL1D/7mpBpAAhosFE9EUi+j8ieie5XA5gFQDTD8RQd5TiA+nszeL0H/wbn5Xs4qWS0URHqSvLvywIcmLliSof+e4pSoDIBRxDyWViJe9NUuIcrgbiCZU859WZsEQp8ZfX7wn7dmRTU0Qm+uub2vzXOpOcb8Lyq/FCCg8Ocl3URERdJ0VZiGWyDmZPHoZ5M0b7glP2gcgIwSE0kXQ2917EOJpTSdgORy5GxHNWBabwAYk/lZB/JI4A6QNHeyEN5HdwTVYrAFwJ4EEAHwHwfmbumywtgyGC8299Lu9ny7e246ElW0I+BSBYPT/0+payr5+1HTQo/8jyShkIVp4Ji/ymTlHk06qiVpyWRX7Yarek8aiNrMICxIk8L5GboS0Lg3FD3VyXXz27Bgd99SE8uWybd51wP5B89yCbZrQaiNLPw5bDg6Vse1EKRcyzJGk//r1LY+hM2xjenEJjMuFrIOk8gQlCoDZKtbBUxP2JplKyZrmrM63dN3ehgdC9hqOwci6ZQ1RPkWpRaFjTmPkjXifC9wM4BsC7mDk3uNlgqANk27XKh25/AZf/fiFeWhOOAK+k30TnA0koYaxp28GsScPQ2pSMqYHkMWFFzCpyHog8mTl5NBCH2Res0aaxcFa5UI6EX2bVtg5vu9wPJH8Yr6XRGnSfh0xYoTwQcV+uyUw9Q6i8iqIFDW1uQGOD5WtOup4kgN6J/tyqHTj0hodxzo+fBXPgNBd10GSt71ylN4cvqJX7FWMV55JHG0c4RH1v1aLQFf3lETPbANYw897qDslgKI1CheR2dLgrQdXvUEkBktb4QNSkPhGCO7gxiQdfK6z1iGPVgnpRq1K5gKP8XEQzosAH4o416zDSdlioaM/rCYOX1+/Gu374DF5aGxbGe7vdKSOsKeTPRJfnxegoLPd9OEFR1qgCDcm9Uc45v6oFuRqI5QcA5BMgqg/k6r8uxnMrd6KjN4vXNrYhYzPe/WNXSLR4Nbjk8uwbdod7c4hxqEJBzbORn1kcH0g9aiCziGiX97MbwOHiNRGZRD5DXSEmr0KoAkM1aZVD1slN8LOUYoqiZHpj0sKOjt6Cgk+NmPLPGzGpyH4HeTXsh716t+xrII6ciZ5/WhDdBeev3YU3NueuJXd3ZbyeGbIZKX8trFC9J435yC8hr6vGK/l5fBOWp4Owf3xwTrVXxuDGpGvC8gWIfhIWvg+5dMyf5wd+rO60je3tvRjSlMTZh7tthbszrmY5Z//hAMKRW1nfhJUbbCHuUYzH/yxWFFb9CZAUgNHezygAjdLrvil1ajDk4ZE3tsbaTw1DzVccrxSydm4+Q0KZQEXJ9CtPdnuybdoT3T1OONFTSbUndrQAkU1YfjtUyZcASD4QZt8XEOlbIde30pPRC93dXWn8/OlVAIA3PQETFcZLode51yUiN6IsXxSWJEDkKrp+0yXpGamO7ROmj3I1kExgwhLH//MzJ+Akr5qzqoG455ei6ryorM+8c7rvE+pOu9cS9bdkIZ71nei5Cw3AbYilhgLHcqLXmwmLme2on1oN0mCIwx3Prom1n7oarmT5k7Tt5GRyq07kjFeGZLxX6XbTHtd/8NyqHXjg1c1QyeYxYUUVH5Sv2Z2xfdOKuHXxmexE//2L6wBEr2TFZC5HXMn0ZGxfMxH+EDmkeNX2Dry1q8vfP22Hn4sOh4Enlm7zxy9rIEEYryvcAguW54im8HlkJg1v9nwgjn9uobEcOmEojjlghHdcOORZ3gYEgsmyyC8oKcykg71EQTkLXiwIdKZOADj+pidwxR8WKTkhxWkgtTJn1V5kGQxVQk3eylfpVhUYlWwDmrW5YBRWOuuasFpS3urUm2w+dPuLuPKPi/KOV60VFRX2LzQFwC0fL6KD1E6IfjFFBxg2qAGjBjdGTlbCHJVPA7Ed9sumt3t1oORM9LN/9CxO/O6T/v53SSHNUaGvoh+KGx7sjUXy84jERbVicJSZrzFpoTGZ8GpXOaEKwgAwdJA7+YvvRzbtqU24AHcCF8+z2xuv0EC6ZAGSN4w3eP/oG1tDxR/jKBeyQNI1oKoGRoAYBgyqvMhnd1cFTSWd6G3dmdzwTAprIMIHIibC3H7pqo9GTPZhE1a0DyS4/660jZbGhHfu8DWFXX9XVxoM4OipIyLvT4QH92ZtraZis2jcBD9E2bKCfihyAENnbzYU4tqbR5Cfd8R436fhOPpGVbJzHdD7QFSEHwpwvxPViS4EiHCIy4JV/oZEWK9lkf9MhFARAuS+Vzb5+6/3NDBVS1DHGrfZmED+PmrlDzECxDBgUCfifKYpdZ6KUxE3Dut2dqKtO5NzXbWYovCB5KtumyMIK2DCGuRpO2oeSLO3/aI7XsL29l5tn+3QvXjmqJ6M42dzh8buMMa0uo2Obv3wbABubkRvxskJVhBZ8Rcc6RZA7MgT0iwL4FB0lxVu4mSR7APJjcJSaZRKtPdmnFATLCAQID2aLn+ydisKSSaI/OMz3ufTx7QCAO59ZaO//9f/+QaAXJ+PKkDW7QxMfXFkia4YZbUplIm+W4rCkn9MFJah7lAn4vwCJDyRVcqJLhoaHT9tVGi7mJOEs1xoIGKVmBMVpo7Pd6LrE890yImEPRkbLSlFA/FeHHPASJxxyFgArvZUyHYuzFE9GdvXNGTkZ37UFFebaUkl0JnOorNXHz49zmu81ZYnik52loer8VqwHcYdz66BLUxYyqQcJWSTCcvX6tzyI2ET1mhPEM4Y15pzbKckVERpk4QVaBWiNP4Bo1vwniPGh8Z10NhW/zMZ9fu89amg7W2cv1DZhFU5nTqaQiJLRFupPyYKy1B35GggkkCRP1M1kHIr+P7rtc248z9r/PPs50XiCHZ6+Scfv9NtZ+N2E7TyFidUFSLRgEgtsxHXhNWdsX1NIzcPxMK5sybEOifgTsi24xUe1NjZn1+9E4+87kbDiSij5sYkunrtUC94eQzDveZb+cKw/ba7DmPD7m5/lX/24fth1OAUbn1qJVgkEipRWIUQ99CbtXNMWAeNbcWvLzkK373g8MhzCCe8RUErXOFXE1pJqPzLqGYcPK614PcpL2wKdXQEFLNVjSRIZDVeNdLKa2Ur/3dsgsFQJ0Q50WVHueobKbeHyKf+EHZ8q6t4MS5RQjzQQIIIKJnc8bnv3zt7AoY3N/j29KgKrWotLJEh7eeBeNdwe4AHx8UxYf3ppfU4euoIbd0oAH5yoVgRt6QSSNsO9nSFBYQYg9BAZns5EznX9CbgpVvc6C5hCpsxthVnHz4ef395I5JWOAorLiIwoTfrhLodAu7rkw/KbaylIib6hOQDESYsIVQcJ7yYicq61xFHIMphwfWigQAAiOjdRLQcbvvZF73fT1RzYAZDsUT5QGQzkbrir3QPEXVyEPOCzewl7DFSifxOdLVft/j8bfsNwXfeG6yGIzUQbwx/eHEdtrX3+lFYgRPdGytRyHZeKN/g/73d1VZefmtPZMIhEKyIhfazuytwmLP3LAC3Mu4TX3gHbnzPodrzCGEoJupzjxgf+txh9qOzfA0k5hQqTFg9GdvVYkpwIwiHuSuMwyYsy8otZZPR5AqJ4/NRtAmrSAd8qcR9XN8EcDyAZcw8CcAZAJ6q1qAMhlKIWsnLDlx1v0p3MVQnArlnhezPUCvN+vtL7zft6cbTy7f55w3F+hcI4wWA6+5dAgAYMdg1E/lFCcUK2Qrb3guZsE4+2F2Rp7Nu/47lN56lFSRJi/zVvIgAk+t+2Q7792kR4YDRg/NqNCIgwJH2D42X3QnTkjSGuVNH+vt89p3T8NV3v0177sFefsw9izbmLWVSCKHdyiYsEZmVsAiWFdaO82ogEQIkTkRWPWaiC7LMvB2ARUTEzI8CmF3FcRkMRaP6zGW5INuTc/NAKrtaU/+RhYbDHKxW5SisnUo5E3l8v3h6Fe5asAGNSQsjmlOhiSdqshP7zRw/BIMbk7hi3oHeGMJ5IO6qOZgGCjUukv0eCYuQSlra6rTyOIVgkCsPu9pY7r46LG8Fz1oBIlrIutuPmzYKq771LhwxaZi/z1WnH4RPnDBVe+6jprhms56MHaogXAyf/8sr/n34GojkAyGlH0zWcfSl6weqCQtAGxG1AHgWwG+J6PsAyl62EdHVRMRENEraNo+IXiGi14noaWn7mUS0jIhWEtGXy722YeARqYE4+X0gb2pqOpWDOgkJ85nNjB8/4UbWpJKWP2F875HlOPi6h4LxSffRk3EwurURL19/Goa3pEAUaCGFEv4AYEtbL06bOVZjwgom44QyIUeRUgSIzP5ebxAgXJBRmInkAoOyBlLIbJSwvP2d8L0BQYi0nASoE0j5nlUyYWHG2MHY05UJdVEsBtmJLu5FLErIe77yn2a+9r1Rzz6OQAiXWolxQAWIK0DeA6AHwOfgmq42Aji7nAsT0SQApwFYL20bBuBWAOcy8yEA3udtTwD4KYCzAMwE8EEimlnO9Q0DD1Uw/Hv5dv+1XCJEFTRLt7RXdBxqiQqxGmUGbvv3agDuBJuvBWlY8Ln+EuFHAIIVfWQYrzeE7nQWTQ1WToa2bA6SJ9xC2oCczBiVCBfKivYc1d2KluU4uRqF9l68jHN/zLLTH0ID4YLaUz6GDUphd1c61EWxFJKWJgrLopxqzNkSTFhxfBqjPDMlEN8HVC5xBcj/ePWvMsz8K2a+BcBVZV77BwCuQVi4fgjAPcy8HgCYeZu3fS6Alcy8mpnTAP4M4Lwyr28YYDgO4z1HjPcT2Dp7A5v7g69tDu0nE4p+rMDSTV1dyhVjBXImuoo8PjXDGgh8CnFMWJ1p2y9ICAQTS9iEFc8sBuSasGTkd/IzaEyI8h6KANGYpLT34kUx6fYnIjDCdayKZVhzA9q6M64Jqww/Qj4TlhrGm08DKUd4AW55ekG9aSBnaraV3JGQiM4FsJGZFysfzQAwnIieIqKFRCTa5k4A8Ja03wZvm+7clxLRAiJasH37dt0uhgGKzYxJI5rxDq+KariAIWPeQe727z+6HNv29gTHhSbs8seRL56/V6r11JCgvKt9dbWqTjaiMGLUZDcoFWgKFuXWiApHYZUoQPKY6oCwPV5oIDkmLCcQYlGI3iaOzoRF8Bs6lTr3D2tu8DWQcuZwK6SBCBOWKLkiB3SwNms8KpE8jnCU/x7qwgdCRJcR0csADiKiRdLPCgBvFDj2MSJaovk5D8C1AK7XHJYEcCRc4XQGgOuIaAagDe/WPiNmvo2Z5zDznNGjTa7jvgIz+6tQXXRTb9ZGk2R+2SCVUJd96JWIyFJNU7pSKY1SFJaKPBHbjpMjKFqFAImYU86dFYS6iuwIIsmJHorCKtEHopjqZMEnnzOoUBuOwoqrgYjCkOK7UaPGHEZZJqzhzSns7sqUHIUlkIWxasKK5wPJf21d2RgdT39xHi48alJ9JBICuAvA4wC+DUB2XLdL5iUtzHyqbjsRHQZgKoDF3qpoIoBFRDQXrmaxg5k7AXQS0b/h9mTfAGCSdJqJMEmMBgnhxwgJEEkypLNOqJptSOtQkryKYeG63Io+6sQqawMC2YmuUsjc4WsgERPO4MakH/4qDpcr9NqSCUs+f+EoLMkHQvEEiBA6sgbSm3V8QVlIA/FLvkiOaX+8XhQWM5U8+Q9tbghyOcoQILIwDgkQKzcKS/0bEfvmY9igeAJk/5EtGN6Sqg8fCDPvZuaVzPw+AIPgOr1PQxllTJj5NWYew8xTmHkKXOEwm5m3ALgPwIlElCSiZgBHA3gTwHwA04loKhGlAFwI4P5Sx2AYeFz865cAANvae4LObiENxAnlK2TzhPUWG9K7antnzjZ1ErrxPYfl7NOQyK+B2IpAy/WBFBYgROSXVRcTrnA4y9dIECkmoegJVBeF9d+nTMcZh4wNPW95yI0aAXLid5/Ep//4sneeyEv6Qk1oIKExekLR5tJNWLLvoJxUCnnxklVNWDF8IOqzHy5pHWOV8jhREOrMB0JEV8LVRiZ7P3cR0RWVHgwzvwngIQCvAngJwC+ZeQkzZwF8GsDDcAXKXcz8eqWvb+i/CJs+I5hwQm1kFQ1E/EN39GbRIzVH6pUihX7+9Crcvzha0RXlSWTUCX9ESwrfPv8wHHtAkNyWSlh5Q0sLCZDDJwwFgFApdB3DvIlRXMbyHM6AFIVlUShiqtAEKmssYlyfP20GfvHROXkbIMnZ3joKNUsS1xHNp3Rhx3KRxWIRAjnOWKJwpDGkJSe6GsabNwpLufZ9V56Ar50zE1efPiNvHosOL7eyJhQyYQkuAzCXmTsAgIi+BeA5uCG3ZeFpIfL7mwHcrNnvQQAPlns9w8AkKKIXmEVyNZDA/JJ1GOt3duGkm58MnUcONb3pX0sBhP0JKj97alXONt3q8oNzJ+ODcydjypcfAJBbWVemUMjnlFFuFVe1OKGKyP3wJybP3LO5rRvX3+euv1QNJE4nu4TlFjeMMmHJnwgN5LWNbfrzxYjCAoJqAvLuakRWKSSK0MCisCU/TGQYb8xSJpNHNuPi4+MLDgGB6q6UCQGQ/1oz0Du2DYY+wQ9T9f5v3PpJwec5GojjTqQquk572/b25F09FxvPL2iIsNuoVYTVCVYIn0I1vESzKHG0G7EEPL9qJwBgxtjBGDKoITSZxZmE/X4cih3fCWkgwXbhA1KLKarny4elmIXUKKy455ngtRAGgkAE9bhiTViymUnWFre0uVF+REGPEDGpu4sCTSZ6hdp51FIDKRSFJZ7y7wC8QERfJaKvwtU+flPtwRkMcRGTilzjSW6elLbD5cezDofCagXdGkEx91uP470/e057Xd1KL05NoqiWo4VMWMKXUyhiTJTLEBOY60QPwmd/ddFROXkgccxAvgCJCOOVJ/mmhgQuPm5K3vMVErhCTsn1pQSqQz2Ke688Hk9dPQ+3f2wOHvzvE4PzFxFE8LtPzA29/7ikITAHz0Su0OuX7fdDqB3t34h8Lz+88Ijom4mgliv7QjLvJQBg5u8CuBRAF4BuAJcz8/eqPDaDITbin0Z2DovXYuKRzUa244R6cAtzj9A01D7pr2/SlzvRtcONYwaK1EAUAaJmtov7KBQxFpQ8cd+7TvwepTwAACAASURBVPSw/0Mdb5wVeEJzHBDWnFQ5NG3M4Lzni+N3AQITlrx/2J8efaLRrY2YMqoFp80ci0kjgrIrxRSTlGtsvfa100MCx2HOyeVISEmc4vvKar5Tsa8/1sGNkeMoRL040f07Yub5zHwLM3+fmedXeVwGQ1GIycPvw2BpBEjCwiOfPwmA63SXiwAKR6rQQOQs9ihKFSBRPpBfPL0K/1m5wz+/Oqn5JqwCAkQIKZEHIsJ45SRCdbxxzG+644CwQFPHHPVMCmk9QRSWLoxX1kYiT5P//EVoMfK+rU0Nofc6c6NlSUEd3qyesfUaSLHfQ17KzGgvhkJO9NFElLdkiVfSxGDoc4LeGoGZww9Z9cwJcuhs1nFCoZWDGxPY0QFs39sLZsbTy+NVMdBpAXHMQFEC5Mll2/H86p1Y+o2z4HCuw9U3YcX0gfiHU9A7AwieWTGZ6O5x7j75SrYAudpA1DMpbMJyP9eZsORDZ00chlIo5v5VQShrL4dPHKatDxaYsBidvVn0ZByMaMnVMERnxpEtKbxt3JCi7kFGjICZy4oqi0MhAZIAMBjGYW6oc8QqO2PnmrAyklDxc0QcDpmphnqJWtf87VVs3NOtTf5TEf6EhKTtAOU70YHAma8reyHMH4U0EOEDCYXxSo2cfE2iiBW4vL96n00Nlj9u9TTyPPalMw/GQ69vweK39uRcX4cf2ZQVTnTpM+nY6RFmsiiKWfmrQxXXP2rKcIzT5GqIMF7ANR+u2+nmDY0bmitAJgwbhAVfPRUjmlNlaSBBRGL1lZFCAmQzM3+9ukMwGMpHtTPL2b9iW1JyGNsOh3wgE4YPwqfmTcNX/v4a3trVhQNGtxS8ppjAG5OWnyR3+syxscarc6LPnToCL60JZ7a7Aiq8nyiVktX04ZAJNJBAE2FIfiJNNFXcMF4gd+K/98rj8dk/vYzlWztyfQHSeT84dxImDh+Ez/zJTSQsNFkKTWeTV34mn5YgZ8kXQzECtBjTHODemzjEYcYnf7MAADBhWLN2/1Fl+j6AYDFVCzdIbB+IwVDPzBjbCgA4f7ZbY1PWQLJyz2pvsuzJOqEoLMcBzjx0HEYPbkRnOusnrUUhzi+bo75w+kGxxqtqICu+eRb+/F/H5F6DOae2VmwNxBIaCPm/RelzQHKiF5lLkc+JfvC4IfiU17gqaqK1LAr1DonrRP/LgrdC41avI4dpF0NRJqwiBYh8TlFReNTgRszJ0/+9Eqg5UdWkkAZyStVHYDBUgNGtjRjZksLZh7tJf65Zyf3M10ASgTnhunuX4OBxrf7xonZQc2MCXWk7JwpLR0ZyzgvixvKrE4/OpJW1HbeWlbqv0EAKhvF6gsN7L/JAbNWEFQrjjTd+3T241whfU90urjtuSGDuKTQJD1Ja3YZNWMHrqNDoKMICKXrffCYsmSkjm7F2Z5f/Xtyf21UROPVtY8pzkhfA94FU7QoBhWph5VaKM9QdjsPY3t5bdCHAgYRajVXOAwmK9oXrT8mNpMSja0kl0dmbRUaTI6L2EdFpIJV0WnZnbG3dJGFyKuREF8dZkgayqzONTs/cptMkipnYdBO/ry1FrNQTFqG1KUjAK7Tql0uNqPvL461IJnpBH0hhDeTxL8wLvZfNq+VUDY6L7AOpNhXKfTT0JdfeuwRHffMxfPGvanuVfQc1hFI2Yel8ICrin605lV8DySgr/qxGgJTbFEimO21rEwnHtjZi7tQR+P77ZkUen7DCTnQC8K8lW/Cjx1cACCbiYkt5CG1N9yyFIqV+pBZsbGqQtbbSBUglnnaxUWihY7395ck6JxJLykQvp2ZXXISQq0VFXiNA+jm2w3h1gxvNsklTmmNfwXZyV9K2r4FIUVh5JyvPhJVKYOmW9lCOiEBd8Yv3sgmr0AQ0c7/44Zldadst/a2cM5mwcNdlx+K4aaMij1cn83x+iXw+hXy8tcv9O9tPE3WUz4QlP/ekRaGVfKEJtSWV34RVCY2vnFImcbQJORPd4Xh+k0pQCw0kbjFFQ53ymT8t8rOkK9ALqd+iZgGLNqhAWAPJ14dctf698lYb9hvahM1tQedCVSsRgkm2vUd1lQOAv33qOHSm4yUpZjwfiK53RBzExBw40cOf6+axYuox6fIufKGUI6yk6yoXLiQDmqNMWN7rVBmFpMLmteLOE+eyvgnLC6GudmhtDfMIjQDp7zz42hb/dSW66fVXckxYUm6G3Lgo3/wgIlbOnz0R976yCe09mZxkP1krWb+zC1/7h1vRVt6v0Ap+UCoRK8cEcHNaMjajocQVq2rCUjOudav3Ylb0uqgnS6PV5DvvmNZGdHs926NoVp3oGo1BVxokLvJziVPH7Np3vc3PG7J8c1Hh8zuOm8RZdRNWDYNnjQDp58yePAyL1u9BSyqxTzvRbdWJTrl5IA0Jq6AGIiai7rSd00Z0S1sPxrS6Zps/vrQeTyx1m3LqmixVgoztuGUvSlxdq6Yred7K9xyKmdx0q/5powfjgNEtuOjYKQXP+8TV82JdT/0edImE5UzKstCII4j+66QD/NdFhfFKiae1wDjRDQUZ3dqIg8e14pgDRoaK2e1rOBoNRORyZEOVUfXHiycnwmm7M3ZOaO2zXn0qIDwZyxNpsfPYO2aEm3vKRQcztoOszQWz1vMRZSrKp4kVs5LXlWOZNKIZT3xhHt59+H6h7bpJc3BjMpY2RkShZlzhjoTetjImZdU/U9SxReTNlNu7PS5+FJZxohsKkbHdyp6WRQXDOvuSnR29mPLlB/CcNAlXEnVlt7mtG/9evh33L94U8oHkM5cIE5aYQLozthKeC/RILVnl3ITBUkhqsSvhOy4+CstuPNN/f++Vx+MHH3Cjq9K2g4zj+BnlxSKOEusKNRdDRzG+hKh6XirlNGoC8vdb9zWQMiZleUIv1gei9vrQIW7dDeOtbKSe9nreb6OBGAqSsR3PNBPuu1xvvOLVPbrtmdVlneeDt72Aqf/zAObc+BjapAZFDocFyI4Ot93rw0u2hGph5UOU9xamHeZwcl9LKomO3kCAyKc685Bx0vYiV7AWhUpwDG5MYrI3lt6sA+b85qaCKCtReWT5VsHFmMuKETblmm3ylYoPzHSlnztRpA8k37H58P0kngmr2hasQAOpPn0qQIjoaiJiIhrlvR9KRP8gosVE9DoRXSLtexERrfB+Luq7UdcXQoBYFhUsbdGXVGrR9cbmvRjRnMKOjl6s3B4kAqqtX4XdfERLyq/Gq5uIj5oyHD//yJG45gy3BIlswhnu9RQX47/jP2vwi6fdFrbyoz5+2sicUNNy8M1onsZTqoM4mLjc96SY+HQUc61iHO7ldtuTF0e6KKxyNBz5z6LYZ11M7TDx/1l1ExYCgVVt+kyAENEkAKcBWC9tvhLAG8w8C8A8AN8nohQRjQBwA4CjAcwFcAMRVa+YTD8iYzMaEuRqIPUsQCoUGZK1HRwyYSgA4BdPB9qMrfTNuOPiowC4k7EchaXSnErizEPHYZgnLGRzkTAlAUB7jxt6+22vT7psUhnWnMLdnzoOHzlmsh+dUw5CgIgCjeWbsDj0G8i/cm4oVdspQLkmrFCiXqh2l7etjElZXlgUex7fhBW1j3fKrFQpuprsKxrIDwBcg/B9MoBWcpc2gwHsApAFcAaAR5l5FzPvBvAogDNh8DWQRJ1rIFEOvd2dafzo8RX4/iPLcN8rG0OfdadtLFy3Cyu3dQBwG0YdMMqtlPvIG1v9xk+qCWv25OGYMGwQ/rZoQ6gWlopqx5dt4OFyG+HjxIr4bM9Z/Lb9huDG9xxWkdVlgx8J5t5bqSYsVQOR/zzym7CqM7mVa8LiPCYsqoAGEjZhFfesR3o9POZOHZF3HzE2EQZebQ1EMGATCYnoXAAbmXmxogb/BMD9ADYBaAXwAWZ2iGgCgLek/TYAmFCr8dYzGS9KRy7dUY+I1dcLq3di455uTBg2yP/s7oUbcMujywG4E805h4/3/8m+/8gy/PLZNSACXvrKqcjYDlqbkrjhnJn433+8gXTWQUsjsHZHV+icgDsRt3Vn/ARA3STW2hT+F8hnA09YBMcOVvKi0dNPPjS7lMcRiRwJ5r4vUQPxDnN8ARL8feQrBV/qtQpRtgbi/b7spAO0fdDLUZxCCahFTu6HThiKF79ySmQLWnHvQUveamsgtVNBqqaBENFjRLRE83MegGsBXK857AwArwAYD+AIAD8hoiHQl7zRPh4iupSIFhDRgu3b43WV68+4GohbpryeBUiPV5ywJ+Pgo798MfTZqxvbMGHYIFx39kzYDvvmIgDY7TnKmYE9XWnfqSw0h4ztYHt7Lzbu6c7xs1w4dzIA4Et/exWA3nSg/uPnC5mVJxaH3dIp1ZoIVBNWqXkgvgkLQvAFn6U1xSKBMhz2BaiUCevYA0eGtlcmDyS451IE6NghTZFaheoDKdcfVAj1e68mVbsVZj6VmQ9VfwCsBjAVwGIiWgtgIoBFRDQOwCUA7mGXlQDWADgYrsYxSTr9RLhaiu66tzHzHGaeM3r0aN0uAwrfiV7nGkhPJohg2tWVDn3Wnc5i6KAGDPP8B3u6g89tKbteVJFtSJJvq884jG8/+CYA4HKvF4VAOLZ7sw4sCiKtZNQGPuoK9J4rjsNN5x8WmmREO9wqzbW5AqREkwcpJiw5c1xX6wuIZ8JSNb04lGvCEtqTKuDz1fkqBjkXpRpJfmJomZppIO7vARnGy8yvMfMYZp7CzFPgCofZzLwFrkP9FAAgorEADoIrcB4GcDoRDfec56d72/Z5RKJZUioeWI/skYSGrix6wiI/cmp7e6//WUbat8vzdzRYVtBUyXawt8fVUuYpSXnNqcA89dlTpmsnh8kjw0JFXYHOnjwcF86dHPKB2A7nJC5WEjGGLs8HUky+hUwwkbjPUNa2MnlyhuIkLT521Tuw+IbTixpLuatu8aedK0w9H0iFJv5qaGCBCSt/MEclCTSQ6lNvpUy+AeBOInoN7nP4EjPvAAAi+gaA+d5+Xze9SlwzxMY93WhIEBKW5Yer1hvPrtiBbz241H+vOvtFCO5Yr8nQn156C3OmuE5J2VbfKYW1ionOLffBmDVxaE5YaUujtLLUTPaPfv6kUOa3e279BCJvz3o1jWpmwirXie69H91auF1qHG1nUCqBQSgubLncZyU0EPX7EcMtV5iL2mnVmNwDE1bhfKRKEGiefd+RsOp4Woh4vQmudqHb7w4Ad9RoWP2C2/7t5iQMaWqAw1y3UVhv7Xa7s33pzIOxo6MXv3t+XehzEUF1yHi31HkqGfyDydn1YkWeTFj+Kj1jM7KOvl6UrIHoVqjTx7bmbItyovvj9TSQakXTCAEizH6lRkaJo8TkK0eVnXLwmMhrV5pKTZrq9+PngZR5ftHXvhpBBIEJy0vorJEJqxaYTPR+zB7PwfyZU6a7GkidmrCEFnHBkRPRnErkNmayXQFCRNhvaFPIlyObsDq9TPBUIijLnvUq1uomflkDkT9/5pqT8dDnTtSONZ8A+dgx+wfjFSUpqiZAhAmrvCgslZR3nhvOmYlfeXkyKtUK423ySr+oGl9cfBOWMj6hnJX7VYiS/FXRQEgsdpzQ+2qzL5qwDEWQdRitTUkMbkwiYSHHiX7dvUuwqzONn3648qGmxSBWXg3exC/6cgdF5tgXCBaF81lsx8GghgS6M3aggVgWGrx/+LTtIGs7IW1DIK+m5YlB50zX7Sfz6XdOw7DmBlx33+uwfRNWrNsvGiJCQ4L8HJdUorQs96BOk/teNvvlo1pRWGOHNOH2j83BjLElChDoqwmIBNVyJ/5UhQXI4htO901I4nsIfCAVuURefB/IQM0DMVQGkYsAuAlwtsNgZhAR5q/dhd+94JqKftqXg0Rg+00mAud3xnaQsNyJ0XYYTQ3k7RPOqM/YjOaUECCSD8T/p3SQdVi7ci6lVSkR4YDRLfivEw/I2S4mGeFEr2Y0TdKy/NpbpTrRBeJx+kJXE8Lb2phEe2+27GtFcdrMsSUfK+5BfeS6XielIOqRZbKVmXXligTiz1Bo3tWOwoLv+9oHfCCG0nGdz+4/fNJfzQMJgh/aCqCq9vo4ZPxaVOQX4MvYjm/WkMuQJBQNJGs7bphlJ/xkw1TC8n0eWUeYsHInvlJLVDzxhXna7eJZu1VVq9vXIaSBlDipW8pEIjSQtCbY4vefPBort3VUpBRLNRB+HPWJi3sqJbRY5sb3HIqv3f86xg4tHGhQLH0VhVULG5YRIP0Y22ZfHRZ/lGJl3yWVHk/bDpqsyhX7u+quVzBlZAs+e8r0WPtn7WACC8JvJTNVSJMKVxXOOowWxTwlO9GFCUvnJ4hqo1oKYoxZh6uaSAi4QsMP4y01kVDJB2hM5jdhzZo0DLMm5baorRs0BSEB4Mj9h+PLZx2MU99WunYDACfNGI0nrp5X1jnyYSk+kJrlgVT1Ki7Gid6PsSXfgVjNf/MBV/PozoQFSDGksw7m3fwk3vm9p3JKXmRsB/cs2uhrA3HIOg6IXOEgNAfZkZ61Aw1JbkUrPlObDslhvFmbPRNW7p+yXNeqEo5LMUa7yomEgCtsO8rUQAJbeOCDAoBMniz0ekb8RahfY1NDApe/48CSnfO1IFjc1boab1UvA8AIkH6N7QST2AWzJwIIkvC6JQ2k2Aljd1caa3d2YfWOzpyscVmziYuo1wXA911kbPYnNkfqE50jQBwnp6WpmkiYsR1t9FSoVWkFNRDbCY+5GjQkLPRk3O+tsVwTVhFO9Hrl5IPcsGO5xH5/QfyZZGsUhWU6EhpiYTuBBjK0uQGHjB/iO6y7M7bfNa9YDaQ3E+z/1wUb8NyqHf5kL8wqxZCxHV9wCE3h+JuewFf+vgSA58tJ5NdAWpsa8KRkXmiQwnjTXttXnYAIOdErIEDE+X7+9Crc98qm6jrRJZNcqQJELaZ4xiHjkEpY+MBRk8sdXs35yrsOxgv/cwpGtPQ/ASL+Tr7vFwyt7vVqGYVlBEg/Ru1ulkxYvoO0J2P7DtFiI0t6soGWcfPDy/Ch21/ECq+ceikaSNYOEv16pXMvXOcWE9i+t9dflalhvBnH1S6meiXcAfc+UyETlj6RUBYqlfinFef7+8tuyfmNe7rLP2keZL9H6aVMwk708cMGYfk3z8JML2GzP5FMWBg3tKmvh1ESqtP8UK+fTbUwPhBDLGQNBHATxTJZxy/vMWSQ63xO28VN+nLhQ4FIWpRNY3KpBNth3PLocuzs6M05NuOwb3/f3RmYxDa39eCPL65He28WSza1AUBOa16ddiGqDwOuiUs01VIpJYw3ClWL6a2iL6GhEgLE+12n+aX7DPKfzYVHTcLE4fnzkCrBPtGR0FA+ahvXhoSFtTs78f5fPA8giEUvdqLrkUxY758z0dvmCg41ukvw+Jtb8aPHV+DIGx/DFX9YiOvuXeLbfLO24wu6XZ2uIBo1OIX2niy+8vfXAABrdnQCcCfprM3oydj46K9exPb23hztQo7mStscOr9MOZ3mtNRwIpYFYvlRWEaC9CXy4mVILcKklei7amIESD/GdpzQxJhMWNjc1oOX1+/BidNH4fSZ4wDkr7yaDyEsfveJufjYsVP8bRv3dOP2Z4I2sj3pQIBslSroPrdqJ373wjqs3O6avbJ2kOj3yROn4pgDRuDuy4/DF70+5AAw2AvVFRrIht1deGbFDswcPwTnzNovNL6GRJBPsrWtJ78GIm2rhONSPJda5Eq0NLrPozFp5S3wWAi1mKKhb5AFSGtj9TMnapnxZfJA+jG2Uo8pJU2YXzv3EGze0wMgf/OgfIiJcnhzCk1eD4merINP3DkfS7e0+/st3rAH89fuwj8Wb8JbuwN/wBXzDsS3HlyKzW09OHjcEM+E5Z5n/LBB+POlxwIALjpuCm5+eBkAoMkL1U1YhJ4MI+35ba6YNw3HHTgqNL6kFUyqP3lyJQBoS5mEfSAVECCe/2ZYcwPaujNlny+KG845BAvW7sL+I1sK75yHwIluREhfIv/tqR0w+ztGA+nHqBpIyG6esPwGQlf+cREef3NrrHOu39mFVdtdc1JTg+WXeOhOZ7FqeweOPWAk/vmZEwAAC9btxi+eXo227gzeKVV3neJNepf9diGeXLoNK7a2a6OkBkurMRF5JaKwhHlMrszr32fSCp3v0ydPw8XHTcnZL1FhAdLtaVzDahBKOm3MYFw4d3JOB75iMD6Q+kBWfmeOr64D3b2eyQMxxEDtX5BUHK+Hjh+KS46fgl2dacxfu7vg+ZZvbcdJNz+J7zzk9u4YMqjBT1C89+VNyNiMdx2+Hw6dMBT7DW3Cjx5fgbTt4L9PmY6fSQUbp45qwfihTUjbDv7rtwuwdEs7DhitX0lfdpJbc0quVGoz++91hQQbLAoJy5MPHo2hzblmJdlsVYkwXhG9dNah48o+Vy244MhJOH/2BFx12oy+Hso+jWzCOqzKEVjAAGlpa6g+bhSWrIGEtZFBqQRuOOcQtKQS2sgqFZGE+MUzDsLdlx+LMa1Nvgnrjc17AQCneSUj3rZfEAo6buigkPBqakjgyndOA+A6+i85fgp+/pEjtdf8xAlT3f2kLN2szb7ZTefb+P/t3XtwlNUZx/HvL7shCcZwsypyERRaRblKUYu30XrBWq13GVqx2lFndNS2TkdqO+I4U2vHa6dq7VRttRZvdZShHbVexl5UECtSvAIKiPWGIAgIJOHpH+95w7ubTbLZ7GbN5vnM7Gz2vCe779mz2Sfn8p6TTlVlBM64lZQtGTSKMQYyYVh/Xr3qGL4zYUiXn6s71PVJceMZExhUX/z1nVz+MrqZS7hYZaw7t7StrA65HuilFWt5+6NoXKEmneKEcYNb/uvvSHIVW2j72oG+fdIZ02/bEgeZQ0bt0rIuUvzlvP6LRqpEy1z822ZMYv67a1m4Yi2Hjs4co6iprqI28aW+c026zU10akJZ4xZHPIi+owsrx+yqrKCSzx9lsRawSw6gF+Pqdlf5kh/9Ui+kmHw93w+kh1v60efMWfBeyyDm0WN2Y+qozC/bC+99mU8T10bUVldxwrg98nr+1l1YuVsjdWE59I7EeZJrT0VXfatlE6Ud55ni8K9+hcOz9iGPjyWDYE07ATG+yjq+eLAqHgNpaYG0Dg7Z01rzuVK7mH+4/eqqufrE/Rhd4N4Wrnfprg2kYt15HYgHkBL684JV3P3vFTTUptm0rZk3P9yQEUDMjHWbt3Hu1JGcPnko0275J+s25z+7p2l75npM2YPosdrqVF5XkMfXfyRbD5K485yvM/OuBXmfV206lfGl3l6LKs43JeyBns4KILmCQ/Z//t3ZAonNzDFo71wuJd//I0vFX4kuabak9yUtCrfjE8dmSVom6S1JxybSjwtpyyRdUY7z7qz1mxsZ0r+OxbOP5ch9dm25mju2eVsz2w12a6hpmbm0cUv+a01lt0CSc8yTXUZ11VV5jYHELZDaPpkfi0GdXH+oOqWMoBGPo+QiiccvO5Q7z5kM5BhEzxEcsoNBW2MgSd39R+xcrFyfvUqfhXWTmU0It78BSBoDnAXsBxwH3CYpJSlFtLHeNGAMMD3k/VLbsKWx5crThtpqPs8KDvFy3fW1aWqro6mpG7d23ALZtLWJOQtW8fmWpoxuqx8ctlfO/H37pHl19WetlmbPtjUOIFkthgF5BpBLjhzFt8fvgaSMoFHXwZjOPrs3sHNt9D6lqkRzc+4urJMnRoPX2eMp+XRh+XiFK5dSLvufy46/j97XhXUScL+ZbQXelbQMmBKOLTOzdwAk3R/yvl6e08zP+i8a6RfWo+pX1/riszig1IdB5vradLstkPVfNLJpaxP3zV/Jrc8uB2DqqB3XCTTU5r5Cun/fKHjNWbCK74Ury3OJWynZX/i77pzfLJ4fHbPjyvLMFkj+m1n1SVexaVtzzkH0608fzy9OHpvzd9pyw+njeWfNxoxZY851p27vwgr3lT4L62JJZwMLgR+b2TpgCPBiIs/qkAbwXlb6gaU6sc82b+P0377Q5edZuXYzR4RB5oa6NBu3NnH0jc+1HI+vbI4vqKuvSfPIK+/z/PJPWz1X83bjnbBeVOyec6cwfmjHu8hdc9L+zFv8Adc/+Tb3vLCyzXyfbtpGKusaC8g9kN2RzDGQ/H9/n8EN3Dd/Fbc8tbTVa6eq1GpzKWi/dXHqAUPzfm3nSqE7Zl4lxfHq8ode5bGLDynpa5UsgEh6Csh1xdWVwO3ANURtrGuAG4Bzyb2Mi5G7qy1nfJV0PnA+wPDhhe17UFWlosywGb1bfcveC8ePHczyTzbRvD2zG+nAkYOYvGc0gHzh4Xvz/PI1bT7fQXsPYtyQfkgwdkj/nMtyP3jBwbwT1qCKDdipDzeeMZ6nOrgafTRRd1Iut82Y1KlAMmKXnZhx4HC2NG5n0vABef/etP1355WV69jS1MywAX1paGfph2tPGcvHG7a2OUXYuS+D2uoUvzxlLMMHlnYV3tiUEQM5ZeKQbln+XuVeqVPSCGCeme0vaRaAmV0bjj0BzA5ZZ5vZsSE9I19bJk+ebAsXLizNiTvnXIWS9LKZTe4oX7lmYSWXVz0ZWBJ+ngucJalG0kiif4oXAC8BoyWNlNSHaKB9bnees3POuUzlGgP5laQJRN1QK4ALAMzsNUkPEg2ONwEXmVkzgKSLgSeAFHCXmb1WjhN3zjkXKXsXVil5F5ZzznXel7oLyznnXM/nAcQ551xBPIA455wriAcQ55xzBfEA4pxzriAVPQtL0idA22t3dGwXoO1LwytTbywz9M5y98YyQ+8sd2fLvKeZtd7sJ0tFB5CukrQwn6lslaQ3lhl6Z7l7Y5mhd5a7VGX2LiznnHMF8QDinHOuIB5A2ve7cp9AGfTGMkPvLHdvLDP0znKXpMw+BuKcc64g3gJxzjlXEA8gOUg6TtJbkpZJuqLc51NMkoZJelbSG5Jek3RpSB8ozY2c7gAABZZJREFU6e+Slob7ASFdkn4d3ovFkiaVtwSFk5SS9IqkeeHxSEnzQ5kfCFsFELYTeCCUeX7Ys6ZHktRf0sOS3gx1fnCl17WkH4bP9hJJcyTVVmJdS7pL0seSliTSOl23kmaG/EslzezMOXgAySIpBdwKTAPGANMljSnvWRVVE9EWwvsCBwEXhfJdATxtZqOBp8NjiN6H0eF2PtFukj3VpcAbicfXATeFMq8Dzgvp5wHrzGwUcFPI11PdAjxuZvsA44nKX7F1LWkIcAkw2cz2J9r+4Swqs67/AByXldapupU0ELiKaIvwKcBVcdDJi5n5LXEDDgaeSDyeBcwq93mVsLyPAUcDbwGDQ9pg4K3w8x3A9ET+lnw96QYMDX9QRwLziLZPXgOks+udaN+Zg8PP6ZBP5S5DAWVuAN7NPvdKrmtgCPAeMDDU3Tzg2Eqta2AEsKTQugWmA3ck0jPydXTzFkhr8QcwtjqkVZzQXJ8IzAd2M7MPAML9riFbpbwfNwM/AeJN6QcBn5lZU3icLFdLmcPx9SF/T7MX8Alwd+i6+72knajgujaz94HrgVXAB0R19zKVX9exztZtl+rcA0hrypFWcVPVJNUDfwEuM7MN7WXNkdaj3g9JJwAfm9nLyeQcWS2PYz1JGpgE3G5mE4FN7OjSyKXHlzt0v5wEjAT2AHYi6r7JVml13ZG2ytml8nsAaW01MCzxeCjwvzKdS0lIqiYKHveZ2SMh+aN4r/pw/3FIr4T3YypwoqQVwP1E3Vg3A/0lxds6J8vVUuZwvB+wtjtPuEhWA6vNbH54/DBRQKnkuv4m8K6ZfWJmjcAjwDeo/LqOdbZuu1TnHkBaewkYHWZt9CEagJtb5nMqGkkC7gTeMLMbE4fmAvEMjJlEYyNx+tlhFsdBwPq4idxTmNksMxtqZiOI6vMZM5sBPAucFrJllzl+L04L+Xvcf6Vm9iHwnqSvhaSjgNep4Lom6ro6SFLf8FmPy1zRdZ3Q2bp9AjhG0oDQejsmpOWn3INAX8YbcDzwNrAcuLLc51Pksh1C1ERdDCwKt+OJ+n2fBpaG+4Ehv4hmpS0H/ks0u6Xs5ehC+Y8A5oWf9wIWAMuAh4CakF4bHi8Lx/cq93l3obwTgIWhvh8FBlR6XQNXA28CS4B7gZpKrGtgDtE4TyNRS+K8QuoWODeUfxnw/c6cg1+J7pxzriDeheWcc64gHkCcc84VxAOIc865gngAcc45VxAPIM455wriAcS5TpDULGlR4tbuas2SLpR0dhFed4WkXbr6PM4Vk0/jda4TJG00s/oyvO4Korn7a7r7tZ1ri7dAnCuC0EK4TtKCcBsV0mdLujz8fImk18N+DPeHtIGSHg1pL0oaF9IHSXoyLIJ4B4k1iyR9N7zGIkl3hC0InOt2HkCc65y6rC6sMxPHNpjZFOA3RGttZbsCmGhm44ALQ9rVwCsh7afAPSH9KuBfFi2COBcYDiBpX+BMYKqZTQCagRnFLaJz+Ul3nMU5l/BF+OLOZU7i/qYcxxcD90l6lGhZEYiWljkVwMyeCS2PfsBhwCkh/a+S1oX8RwEHAC9FSz1Rx44F85zrVh5AnCsea+Pn2LeIAsOJwM8l7Uf7y2nneg4BfzSzWV05UeeKwbuwnCueMxP3LyQPSKoChpnZs0QbW/UH6oF/ELqgJB0BrLFof5Zk+jSiRRAhWiDvNEm7hmMDJe1ZwjI51yZvgTjXOXWSFiUeP25m8VTeGknzif4xm571eyngT6F7SkT7c38maTbRjoGLgc3sWIr7amCOpP8AzxEtU46ZvS7pZ8CTISg1AhcBK4tdUOc64tN4nSsCn2breiPvwnLOOVcQb4E455wriLdAnHPOFcQDiHPOuYJ4AHHOOVcQDyDOOecK4gHEOedcQTyAOOecK8j/AQt6t/roAHl7AAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"window = 10\n",
"plt.xlabel('Episode')\n",
"plt.ylabel('Total Reward (SMA 10)')\n",
"plt.plot([np.mean(total_rewards_a[tr:tr+window]) for tr in range(window, len(total_rewards_a))])"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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