Artificial Intelligence

Module 1: Logistics and Introduction


Executive Summary

  • Topics: This module will cover the following topics.
    • Course logistics: How this course will work as an asynchronous online class.  You will learn how the content will be integrated with Canvas and how to work both within Canvas and on the course website. 
    • Project introduction: You will learn what the course projects will look like and you will start your first project.
    • Introductions: You will sign up for the course slack and introduce yourselves
    • Intelligent agents:  You will begin content in the book, starting with chapter 2 on intelligent agents
  • Length: The content of this module will take one week to complete.  Any module with an associated project will remain open for the project only beyond the expected time period for the content.  
  • Assigned chapters: Chapter 2
  • Project: This module assigns Project 0.  The project portion of the module will remain open for one week beyond the module content.


Course logistics

Course structure 

  • The course is organized into themes and topics, which are listed as modules on the main course website.
  • Make sure you take the quick course tour in Module 0!
  • There are 3 cross-cutting modules at the bottom of the main course website.  We will introduce each one below but this is a quick overview.
    • The Projects Module will collect all information on the project (which will be active throughout the semester).   
    • The In-The-News Module will feature a semester long discussion of how AI shows up in current news. 
    • The Information Module will contain links to important information like the syllabus, the online classroom code of conduct, and a copy of the weekly announcements.
  • At the start of each week, I will summarize the plans for the week and post in #announcements on slack
  • Canvas will have all of the grades

Class expectations:

  • I assume you will spend about about 6-9 hours per week on class.  If this was in person, we would have 3 hours of lecture/discussion and 3-6 hours of homework assignments, reading, and project work per week.  Remember, the class is completely asynchronous. I have assignments and expectations for you due each week but you decide on your schedule.  
  • I assume you will be an active participant in class!  Ask questions of myself and your fellow students.  Engage in the material and join the discussions! 
  • I expect you to adhere to the class code of conduct and to be respectful at all times in your discussions.  See the assignment below for more. 

Class schedule:

  • I have structured the deadlines to space out the assignments through the week.  This is to help you remain engaged all week.  However, it is an online class and flexibility is great!  As you will learn when we discuss grading, the deadlines are flexible.  Each assignment and grading declaration will close Sunday 11:59pm for that week, even if I ask for you to complete the item by an earlier day.

Class tools:

  • Because we are sharing this material across AI2ES we will share course materials on the AI2ES course website. 
  • For OU students, canvas will store all grades/points and links to all assignments
  • Slack will manage all discussions and DMs – Slack will be our main mode of communication!

Required course materials:

  • The required book is the fourth edition of “Artificial Intelligence: A Modern Approach” Make sure you buy the fourth edition as it is significantly updated and we will be using the new materials.  Readings from this book will be referred to as AIMA for the rest of the semester.  There is an online edition which is quite nice and hyperlinked.
  • There will be some additional reading beyond the book but it will be freely available and linked through the webpage.

Announcements: Announcements will go on slack on the #announcements channel AND on the information module here.

Accommodations: If you need accommodations, please register with the Office of Disability Services and they will email me.  Please feel free to contact me with any concerns or questions that you have about any kind of accommodations you think you might need. Online classes are really flexible, and I am sure we can come up with a good solution for any concerns you might have. Just let me know!

Contact me anytime! I hope you will find answers to all your questions about how class will work as you work through the first week of activities.  However, please feel free to slack DM me, ask on a public slack channel if it of wide interest, or even email me.  I don’t always check messages instantly in the evenings or on the weekends, but I am at work every day, Monday through Friday (and if I’m going to be out of the office during business hours, you’ll see a note about that in the announcements).

Have fun in class! I look forward to working with you on class and to having fun learning together!

Topics for Module 1

Topic 1: Syllabus & Setup

  • (10 min) Learn what we will be covering in this class
    • (5 min) Make sure you read the course logistics above (in this page)
    • (5 min) Class overview
      • Watch the video giving you an overview of class.  Every video will also have a link to a pdf of the slides just below it in case those are useful for you.  For complicated topics, I will also provide both video and text explanations.  I do not do that for the introduction since this is just a class overview.
      •  Link to the slides
    • (3 min) Project overview
      • The video below gives a demo of the project system and explains the kinds of projects we will be completing this semester.
  • (30 min) Syllabus & class expectations
    • (5 min) Watch the class logistics overview video to learn how the class will be structured
    • Watch the syllabus highlights AND Read the syllabus
    • Read the code of conduct
      •  Complete the code of conduct “quiz” (this is not really a quiz, just agreeing to follow the code of conduct)
    • What is a grading declaration?
      • You should have noticed in the syllabus that I listed something called a grading declaration.  These are drawn from a philosophy called Ungrading (you do NOT need to purchase or read the book, I’m just linking to it in case you want to learn more than you do from the quick reading below.  If you really like the idea, there is an crowd-sources open-access book on Ungrading also!).  While we are not doing full ungrading this semester, we do use many of the approaches to improve your learning experience.  For example, rubrics are an ungrading technique where you know exactly what points are assigned for what and you choose how many you want to achieve.  They are also useful for grading transparency!  We will also make use of something called grading declarations.
    • Bug hunting
      • No online class is every fully perfectly put together.  For each module, there will be extra credit points for the first to find bugs where bugs can include broken or wrong links or anything on the webpages or quizzes.  Most likely bugs will be links to last year’s class accidentally not updated in this year’s pages so keep an eye out for accidentally getting redirected to ai-fall2021!  Project bugs have separate track for bugs – this is only for the class content itself.  To earn the extra credit, you must
        1. Be the first to report report the bug to the #class-bug-reports channel
        2. Have the bug be verified by Dr McGovern (e.g. if you report a broken link and it isn’t broken, it isn’t a bug)
  • (30 min) Class discussions
    • Set up your account in slack via the link in canvas.  Make sure you use the name you wish to be called but please don’t use your online or gaming nickname (e.g. I need to know who you are, not “AINerd4”)
    • Introduce yourself in the introductions channel.  Answer the following questions:
      • Who are you?
      • Why did you enroll in this course and what do you hope to get out of it?
      • Answer the questions embedded in the overview video
    • Learn how to use emojis and wave at your fellow students virtually in slack
    • Learn how to use threads in slack.  Reply to other students on their introduction thread.  Reply to at least 3 of your fellow students by Wednesday.
    • Complete the slack grading declaration on canvas (called “Module 1: Slack introductions“)

Topic 2: Effective Online learning 

Some of you may already be used to taking asynchronous classes but it may be new to others.  I want to see you succeed and thus I’m giving you some tools to help!  

Topic 3: Intelligent Agents

After you are ready for the online asynchronous class experience, it is time to move to topics for AI!  For this module, we will work on one of the introductory chapters.  Each module will have readings and videos.  You could do the readings and then the videos or the videos and then the readings, whichever you find best for your learning style!

  • (30-45 min) Read chapter 2 (Intelligent Agents) in AIMA 
    • Chapter 2 focuses on characterizing what we mean by intelligent agents and critically assessing the environment in which the agent will perform.  After you read the chapter, go through the highlight videos below and then there will be exercise that covers all of the concepts. 
  • (5 min) Specifying the agent using PEAS: Performance, Environment, Actions, States
  • (10 min) It is important to understand what the environment looks like where the agent will be acting. 
  • (5 min) What are the general types of intelligent agents that we will discuss this semester?
  • (30 min) Complete the homework assignment on agents and environments


Project 0

Your first project will focus on helping you learn how to use the project system.  This will be the same project system we will use all semester.

  • Task 1: Read about the projects in general
  • Task 2: Read the description for Project 0.  This is assigned this week and due in two parts, one this week and one middle of next week.
    • Project 0 Part 1: Due Aug 26 11:59pm
    • Project 0 Part 2: Due Aug 31 11:59 pm

Suggested schedule for module 1

Week 1 (Aug 23-29)

  • Complete Topic 1 by Tuesday
  • Complete Topic 2 by Thursday
  • Complete Topic 3 by Friday
  • Complete part 1 of Project 0 by Friday
  • Complete part 2 of Project 0 by next Wednesday
  • Easter egg:  Make sure you find and do the voting module and assignment on Canvas