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update notebooks
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5 files changed

+66
-87
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‎notebooks/blackjack.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 1,
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"id": "900376a8-792f-41bc-988c-2bc23ff2d7d4",
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"metadata": {},
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"outputs": [],
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"source": [
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"import gymnasium as gym\n",
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"from utils.blackjack_wrapper import BlackjackWrapper\n",
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"from utils.test_env import TestEnv\n",
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"from algorithms.planner import Planner\n",
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"from algorithms.rl import RL\n",
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"from bettermdptools.utils.blackjack_wrapper import BlackjackWrapper\n",
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"from bettermdptools.utils.test_env import TestEnv\n",
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"from bettermdptools.algorithms.planner import Planner\n",
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"from bettermdptools.algorithms.rl import RL\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 2,
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"id": "265aae24-a1b3-4400-8bcc-8da16e9a4612",
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"metadata": {},
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"outputs": [
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"output_type": "stream",
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"text": [
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"runtime = 0.03 seconds\n",
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"0.2\n"
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]
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},
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"name": "stderr",
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"text": [
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"runtime = 1.34 seconds\n",
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"0.01\n"
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"runtime = 1.30 seconds\n",
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"0.1\n"
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{

‎notebooks/frozen_lake.ipynb

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"outputs": [],
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"source": [
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"import gymnasium as gym\n",
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"from algorithms.planner import Planner\n",
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"from utils.plots import Plots"
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"from bettermdptools.algorithms.planner import Planner\n",
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"from bettermdptools.utils.plots import Plots"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"runtime = 0.51 seconds\n"
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"runtime = 0.42 seconds\n"
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{

‎notebooks/other_utilities.ipynb

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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"execution_count": 1,
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"id": "4815068f-bb52-47fb-9d35-3a340663c758",
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"metadata": {},
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"outputs": [],
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"source": [
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"import gymnasium as gym\n",
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"from utils.test_env import TestEnv\n",
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"from utils.grid_search import GridSearch\n",
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"from utils.blackjack_wrapper import BlackjackWrapper\n",
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"from algorithms.rl import RL\n",
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"from algorithms.planner import Planner"
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"from bettermdptools.utils.test_env import TestEnv\n",
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"from bettermdptools.utils.grid_search import GridSearch\n",
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"from bettermdptools.utils.blackjack_wrapper import BlackjackWrapper\n",
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"from bettermdptools.algorithms.rl import RL\n",
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"from bettermdptools.algorithms.planner import Planner"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 2,
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"id": "448dc393-ba4f-412d-ac89-6c71a22cfeaf",
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"metadata": {},
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"outputs": [
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"runtime = 0.67 seconds\n",
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"runtime = 0.64 seconds\n",
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"Avg. episode reward: 0.0\n",
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"###################\n",
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"running q_learning with gamma: 0.99 epsilon decay: 0.9 iterations: 5000\n"
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]
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},
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"name": "stderr",
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" \r"
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"output_type": "stream",
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"text": [
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"runtime = 6.56 seconds\n",
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"runtime = 6.49 seconds\n",
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"Avg. episode reward: 0.0\n",
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"###################\n",
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"running q_learning with gamma: 0.99 epsilon decay: 0.9 iterations: 50000\n"
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]
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"text": [
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"runtime = 53.30 seconds\n",
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"Avg. episode reward: 0.83\n",
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"runtime = 54.57 seconds\n",
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"Avg. episode reward: 0.88\n",
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"###################\n"
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]
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},
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"cell_type": "code",
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"execution_count": 3,
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"id": "60161c93-6183-4de6-a937-7c12b9742fb7",
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"metadata": {},
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"outputs": [
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"text": [
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"running VI with gamma: 0.7 n_iters: 500 theta: 0.001\n",
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"runtime = 0.02 seconds\n",
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"Avg. episode reward: 0.01\n",
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"runtime = 0.01 seconds\n",
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"Avg. episode reward: -0.16\n",
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"###################\n",
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"running VI with gamma: 0.7 n_iters: 500 theta: 1e-05\n",
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"runtime = 0.02 seconds\n",
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"Avg. episode reward: -0.07\n",
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"Avg. episode reward: 0.18\n",
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"###################\n",
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"running VI with gamma: 0.9 n_iters: 500 theta: 0.001\n",
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"runtime = 0.01 seconds\n",
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"Avg. episode reward: -0.16\n",
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"Avg. episode reward: -0.06\n",
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"###################\n",
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"running VI with gamma: 0.9 n_iters: 500 theta: 1e-05\n",
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"runtime = 0.02 seconds\n",
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"Avg. episode reward: 0.01\n",
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"runtime = 0.01 seconds\n",
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"Avg. episode reward: -0.1\n",
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"###################\n",
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"running VI with gamma: 0.99 n_iters: 500 theta: 0.001\n",
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"runtime = 0.01 seconds\n",
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"Avg. episode reward: 0.13\n",
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"Avg. episode reward: -0.1\n",
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"###################\n",
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"running VI with gamma: 0.99 n_iters: 500 theta: 1e-05\n",
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"runtime = 0.01 seconds\n",
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"Avg. episode reward: 0.07\n",
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"Avg. episode reward: -0.04\n",
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"###################\n"
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]
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}
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"id": "c329484d-db1b-48fe-b7a0-b035ad5356bb",
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"metadata": {},
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"source": [
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"RL algorithms SARSA and Q-learning have callback hooks for episode number, begin, end, and env. step. To create a callback, override one of the callback functions in the child class MyCallbacks. Or, you can use the add_to decorator and define the override outside of the class definition. For example, print the episode number every 1000 episodes."
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"RL algorithms SARSA and Q-learning have callback hooks for episode number, begin, end, and env. step. To create a callback, override one of the callback functions in the child class MyCallbacks. Or, you can use the add_to decorator to define the override outside of the class definition. For example, print the episode number every 1000 episodes."
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]
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}
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"source": [
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"from utils.decorators import add_to\n",
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"from utils.callbacks import MyCallbacks\n",
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"from algorithms.rl import RL\n",
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"from utils.blackjack_wrapper import BlackjackWrapper\n",
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"from bettermdptools.utils.decorators import add_to\n",
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"from bettermdptools.utils.callbacks import MyCallbacks\n",
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"from bettermdptools.algorithms.rl import RL\n",
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"from bettermdptools.utils.blackjack_wrapper import BlackjackWrapper\n",
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"\n",
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"base_env = gym.make('Blackjack-v1', render_mode=None)\n",
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"blackjack = BlackjackWrapper(base_env)\n",

‎notebooks/plots.ipynb

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"outputs": [],
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"source": [
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"import gymnasium as gym\n",
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"from utils.test_env import TestEnv\n",
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"from algorithms.rl import RL\n",
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"from algorithms.planner import Planner\n",
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"from utils.plots import Plots\n",
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"from utils.blackjack_wrapper import BlackjackWrapper\n",
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"from bettermdptools.utils.test_env import TestEnv\n",
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"from bettermdptools.algorithms.rl import RL\n",
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"from bettermdptools.algorithms.planner import Planner\n",
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"from bettermdptools.utils.plots import Plots\n",
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"from bettermdptools.utils.blackjack_wrapper import BlackjackWrapper\n",
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"import numpy as np\n",
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"import seaborn as sns\n",
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"import matplotlib.pyplot as plt"
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"runtime = 0.57 seconds\n"
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"id": "5a1642ef-4a93-4d08-96f7-d62b58a63e58",
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"metadata": {},
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"cell_type": "code",
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"id": "8b7c01ed-cb3e-45d5-9f88-c8733ae3c6f0",
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"metadata": {},
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"id": "31f641c6-d465-4c49-a7bc-770a0aaebe12",
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"source": [
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"### Using the add_to decorator to make changes on the fly. "
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"### Customized policy map using the add_to decorator. "
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"source": [
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"from utils.decorators import add_to\n",
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"from bettermdptools.utils.decorators import add_to\n",
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"\n",
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"@add_to(Plots)\n",
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"@staticmethod\n",

‎notebooks/taxi.ipynb

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"outputs": [],
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"source": [
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"import gymnasium as gym\n",
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"from algorithms.planner import Planner\n",
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"from utils.plots import Plots\n",
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"from utils.test_env import TestEnv"
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"from bettermdptools.algorithms.planner import Planner\n",
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"from bettermdptools.utils.plots import Plots\n",
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"from bettermdptools.utils.test_env import TestEnv"
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"text": [
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"runtime = 0.04 seconds\n",
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"[ 5. 10. 6. 4. 11. 9. 8. 6. 8. 6.]\n"
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"[12. 8. 11. 8. 8. 6. 8. 7. 10. 8.]\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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""
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]
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}
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],

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