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Notebooks/Chap19/19_1_Markov_Decision_Processes.ipynb
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58
Notebooks/Chap19/19_1_Markov_Decision_Processes.ipynb
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"authorship_tag": "ABX9TyMForqbtn4usiIlRAenjCfh",
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"include_colab_link": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"id": "view-in-github",
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"colab_type": "text"
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},
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"source": [
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"<a href=\"https://colab.research.google.com/github/udlbook/udlbook/blob/main/Notebooks/Chap19/19_1_Markov_Decision_Processes.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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]
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},
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{
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"cell_type": "markdown",
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"source": [
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"# **Notebook 19.1: Markov Decision Processes**\n",
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"\n",
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"This notebook investigates Markov decision processes as described in section 19.1 of the book.\n",
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"\n",
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"Work through the cells below, running each cell in turn. In various places you will see the words \"TO DO\". Follow the instructions at these places and make predictions about what is going to happen or write code to complete the functions.\n",
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"\n",
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"Contact me at udlbookmail@gmail.com if you find any mistakes or have any suggestions."
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],
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"metadata": {
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"id": "t9vk9Elugvmi"
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}
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},
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{
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"cell_type": "code",
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"\n"
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],
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"metadata": {
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"id": "OLComQyvCIJ7"
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},
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"execution_count": null,
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"outputs": []
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}
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]
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}
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