Artificial Intelligence


Information Module

AKA the module that holds all the important links (syllabus etc) plus a listing of all the weekly announcements

Syllabus

Other important links

  • Virtual classroom code of conduct
  • Don’t forget to join slack!!  The link to join is on canvas in the quiz for module 0.

Weekly announcements and what is due

Week 1

Welcome

Welcome to Artificial Intelligence!!  I am very excited to have you in class this semester and am looking forward to our learning journey together!

This announcement is also available as a video! 

 

We are a fully online asynchronous class 

OU is offering AI class twice a year right now, once a year in a fully online format and once a year in-person.  This is our online semester so everything this semester is online and asynchronous.  If this is somehow not what you were expecting, you should consider waiting for the spring offering of AI when it will be in person.  

 

Weekly announcements

Every Monday morning, you will get a slack message on #announcements from Dr McGovern, telling you what we are doing this week. ALL announcements except this one will go ONLY to the slack #announcements channel.  This one is copied to the canvas announcements board and sent out as a message in canvas to all enrolled students but make sure you join slack for all future communication.

 

What you are working on this week

For this week, you will actually complete TWO modules.  I promise, this is the only week you have two modules and one of them is very short. 

  • Module zero is a tour of the course and how the logistics will work.  You will complete this in the first few days of the semester!
  • Module one is an overview of course expectations, syllabi, class code of conduct, and then it jumps into an introduction to intelligent agents. 

Note, we are also going to jump right into the projects this week!  Project zero is a necessary but short project to get you to understand the project system and to be able to create your accounts on the project submission machine.  

 

Special notes for this week

Two last quick notes for the semester:

  • There is currently no TA for the course and there are 60 of you and only one of me.  This means I will do my best to reply in a timely manner and to ensure that your grades are always up-to-date but I am only one human and I may fall behind at some point due to life circumstances.  Please be understanding with me as I am understanding with you on any of your life circumstances.
  • Related to the above:  I am the director of a large NSF institute (the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES)).  This year NSF decided to have our annual site-visit on the fist Monday and Tuesday of classes!  This means I will not be immediately responsive to your emails or slack messages.  I will get to them in the evening on both days but I will be unable to respond during the day until Wednesday.  This also means I will not be holding office hours until Wednesday!

 

I look forward to working with you this semester!

Week 1 – second announcement

I sent my usual Monday morning announcement on Saturday but I wanted to say good morning and welcome to the semester!  This will be the last message that goes through canvas and slack at the same time.  Don’t forget the class is almost entirely hosted outside of canvas at https://ai-fall2022.ai2es.org (but all grades & assignments are on canvas, linked from the class webpage).  I look forward to working with you!

Week 2

Welcome to week 2 of AI!  I hope you are excited by all of your classes this semester and ready to jump into AI even more!  Your weekly announcements are below and, as before, also available as a video.

What you are working on this week

  • This week we move to module 2.  As I promised before, we will only have one module at a time from now on.  Module 2 focuses on intelligent search methods, starting with methods where the agent has very little information and moving to methods where the agent has information to help guide the search.  As expected, if you give it more information, you will get a more efficient search that produces better results!  This module has a lot of methods in it and will take 2 weeks to complete!
  • This week you will also finish project 0.  Because the final step of project 0 is relatively simple and I want you to move to project 1 (where you actually begin coding), this is due in the middle of the week:  Wednesday Aug 31!  Please make sure you pay attention to the help videos in project 0 to show you how to submit.  Once you submit, I will run a ladder on Thursday morning and you will be able to see if your agent ran correctly.  While this is not worth a lot of points, it is critical that you complete project 0 or else you will be unsure how to submit project 1 code!
  • The other project item to work on this week is finding a partner!  This is not required – you can do the projects alone if you want.  But I will allow sets of two people to work together.  Project pairs are required to be turned in by Sep 6 on canvas (see instructions in Project 1).  Feel free to discuss in #general or #projects if you are looking for a partner!

 

getting help when you are stuck

  • If your question does not involve sharing code, please post in #projects or #homework depending on the nature of the question.  With no TA, you are likely to get help faster from each other and from me than if you only email me.  
  • If your question is very specific to you (e.g. you can’t login, you need to show me code that isn’t working, etc), please DM me in slack. 
  • If you want to see me in person, I will hold one in-person office hours a week.  If you prefer zoom, I will also have an additional zoom only office hour per week.  Plus I am answering slack DMs and messages in the channels!  To keep the zoom URL private, it is available ONLY in slack and not on the webpage where I archive announcements.  

 

Grading

  • Without a TA, the grading is just being done by me.  Remember there are 60 of you!  I’m working to grade each day, once a day, to hopefully keep up with it. If you have a specific question about the grading once it is complete, please ask but please be patient as I work to ensure grading is caught up.  I will aim to always be within the 2 week guideline for OU but my specific goal is to be within a day or two, except if I am traveling (which will happen once this semester).

 

Looking ahead

  • I’m working to get all of the modules open over the next few weeks.  This week I added project 4 and module 5 to the list of open modules.  Over the next few weeks, I’ll get them all up and running!

Week 3

Welcome to week 3 of AI!  Your announcement is coming out on Tuesday instead of Monday because of the holiday.  I hope you had a good holiday weekend!  If you prefer video over text, the announcement is below.

What you are working on this week

  • This week you are finishing module 2 – intelligent search.  Last week focused on search methods where the agent had little to no information on the search.  This week we move into more intelligent methods where the agent has information to guide its search and thus can be more efficient in the search and provide better answers!
  • This week you also work on project 1!  Remember you have a deadline for project 1 TODAY!  You need to turn in your partner list today.  Partners are not required but they are encouraged! Turn them into the right canvas assignment so I can make your teams.

 

Project 1 help

  • A lot of you have asked about how to implement a graph in space settlers.  I prepared a special video to help you out! So that you can easily find it while working on the project, it is on the project 1 page.  It is also linked below just to make it easy to find!

 

Deadlines

  • There seems to be some confusion on deadlines:  I have deadline spread throughout the week in order to keep you on track!  You should NOT be going until the final Sunday of each module and then frantically trying to catch up.  This will not lead to success.
  • On a related note: Projects are NOT due on Sunday.  For example, Project 1 part 1 is due TODAY!  and Part 2 is due on a Friday (Sep 16, next Friday)!

 

Looking ahead

  • Module 6 is now open! 

 

Week 4

Welcome to week 4 of AI!  Your weekly announcement is below and available in video format as usual if that is easier!

What you are working on this week

  • This week we move to a short one-week module:  Module 3 which focuses on making search work in the real-world.  While all of the methods we discussed in module 2 can work, they need some adaptation to work in environments outside of the textbook and that is what we discuss in that module. 
  • Module 3 will be helpful to you for your projects, which is why I encouraged anyone who was stuck to look ahead there.  Hopefully my video from last week also helped with the project!

Project 1

  • Reminder: Project 1 is due THIS WEEK, on Friday at 11:59pm!  
  • Don’t forget about the extra credit ladder!  This is also a great way to test your project code out in the real conditions of the ladder.  The ladder has been up and running since last week, as promised, but no one has submitted yet, which makes me think no one remembers the extra credit chances!  Remember, you can earn extra credit in two ways: 
    • Being the top of the competitive ladder  
    • Outperforming the heuristic-based agent in the cooperative ladder
  • I will only grade your final submission to the ladder so if you submit non-final code just to see if it runs and works ok, that is precisely what the ladder is there for!  To give you a chance to test your code and a chance at extra credit also.  

Discussions

  • You are all doing a great job of keeping up on the discussions in google docs this past week, which is great to see.  The idea of discussing in the docs was a new experiment and I am glad it is working.   We tried some of this in slack last year and slack just doesn’t allow for the annotations and threading and replies the way we wanted.  Thank you to those who participated in the poll about the google docs, I will keep it up sporadically through the semester (not all modules lend themselves to it).

Looking ahead

  • Modules 7 & 8 are now online!  The only pieces remaining to go live are modules 9 & 10 and projects 5 & 6.  Note, the first 5 projects are all programming in spacesettlers while project 6 will be a creative project (that can still involve programming if you want but it will not be required).  

Week 5

Welcome to Week 5 of AI!  As usual, your announcements are available as a video as well as below.

Important – no office hours this week!

  • I am on business travel this week and thus will NOT be available for office hours.  I will do my best to keep up with the slack questions morning and evening but they have my schedule very full during the day.   I’ll also try to keep up on the grading as much as possible but it is possible I’ll end up doing a major grading catch-up once I’m back.

What you are working on this week

  • This week we move into a new two week module focusing on adversarial search aka how to search in games!  This is a fun module and there will be a project on this (Project 3!) though it will not be assigned until you finish Project 2, of course.

Project 2

  • Project 2 begins this week!  This is basically an extension of project 1 where you will focus on making informed searches instead of uninformed searches.  Everyone will be doing A*.  
  • Don’t forget about the extra credit ladder!  This is also a great way to test your project code out in the real conditions of the ladder.  The ladder will be open all week!
    • I will only grade your final submission to the ladder so if you submit non-final code just to see if it runs and works ok, that is precisely what the ladder is there for!  To give you a chance to test your code and a chance at extra credit also.  

Looking ahead

  • Module 9 is now online!  Next week I hope to release the final module (10) and the remaining 2 projects.

Week 6

Welcome to week 6 of the semester.  You have completed more than 1/3 of the semester at this point! 

Mid-semester thoughts

Since it is Monday and I know we are starting to get into that part of the semester where everything feels overwhelming (and I get that, it looks that way for faculty too!), I wanted to share a Monday morning thought with you about workload. 

  • When it all feels overwhelming, step back and take a few deep breaths. 
  • Then write down on a piece of paper (or an electronic list) ALL the items that are cluttering up your head and worrying you about getting things done. 
  • Then take a few more deep breaths and realize, you can do this!  The way you do it is to do one step at a time and make progress.  Don’t try to tackle it all at once. 
  • Take that list and prioritize and start on the big items.  The others will come along as you get stuff done!

Catching up on grading

Related to the discussion:  being out for a week put me behind on grading!  I’m working hard to catch up.  I finished all of the undergraduate submissions for project 1 last night and I aim to have the graduate ones done by Tuesday-Wednesday.  Then I will start on project 2 grading.  Hopefully will be all caught up by this weekend but please be patient with me as I’m only one of me and there are a lot of you!

What you are working on this week (module and project)

  • This week you are finishing the module on adversarial search!  It should be fun as you learn about the more advanced ways to handle search in large games.
  • Your next project (Project 3) will be on adversarial search!  Once the 3 day late deadline expires for project 2, I will update the configuration files for the project and you can do a git pull (I’ll make an announcement in #projects and #announcements) and you will suddenly have gaming asteroids.  If you want to do it yourself, you can go into the SpaceSettlersConfig.xml and turn on gaming asteroids.  

Looking ahead

  • My travel included some unplanned adventures like food poisoning so I didn’t get module 10 ready as I had hoped.  My new goal is next weekend but first I want to catch up on all the grading for you all!

Week 7

Welcome to week 7 of AI!  With 15 weeks to the semester, this week marks our halfway point (halfway through the week!).  Keep it up – you are doing great and you can do it!

What are you doing this week?

  • This week we start our last module on non-machine learning based AI techniques.  This module is a combined module on traditional planning techniques and multi-agent systems.  I know that multi-agent systems researchers also use machine learning techniques in their work.  The way this is structured is that this module is a combined introductory module for planning and multi-agent system concepts.  We really can’t talk about how to use ML for multi-agent systems until we have learned some ML so first we will jump into planning and multi-agent systems and then in two weeks, we will jump into machine learning!  Module 5 is a two week module.
  • You are also working on project 3 this week!   It is due at the end of this week (halfway through the module).  This one focuses on minimax search with the gaming asteroids.  Make sure that you do a git pull on the code to ensure you get the right configuration files and that you get the bug fix submitted by one of your fellow students!

Grading status

  • I finished all of Project 1 grades and will finish Project 2 by this weekend.  That should fully catch us up before Project 3 is due 🙂

I hope you all have a lovely fall break this weekend and I hope you are enjoying all the fall weather!  Don’t let mid-semester stress get you down (we faculty feel it too!).  I look forward to continuing to work with you in slack, office hours, etc.

 

Week 8

Welcome to week 8!  You made it over the halfway point!!  I hope you all had an awesome fall break – I wish it was longer but just to let you know now:  I’m giving you the full week of Thanksgiving off so you will have a second break in a month.  I know the semester is hard & long and we all need to take mental breaks to recharge ourselves!

What are you doing this week?

  • This week we finish the combined planning & multi-agent systems module.  This is your final module before we dive into machine learning (next week!).
  • Project 3 is done!  
  • I think that Project 4 is the hardest project all semester and thus I give you a LOT more time for it.  It is available now and due Oct 30.  I strongly suggest that once you are done with Project 3, you look at Project 4 and start asking questions in the #projects discussion!

Looking ahead

  • For those who like to plan ahead:  there are 3 projects left.  Project 4 is on planning & multi-agent cooperation and the spacesettlers game changes a bit (read the description for more).  Project 5 is going to be on learning in spacesettlers.  Project 6 will be a non-coding project and instead will be a creative writing project.  I promise it is lots of fun too!
  • Next week we will start machine learning.  We will focus on that for 4 modules and then we will finish with a module on AI & ethics

See you in slack and office hours!

Week 9

Welcome to week 9 of AI!  

What are you doing this week?

  • This is our first week to jump into machine learning!  For the next four weeks, we will do one new machine learning module per week.  We will also have a project on machine learning (Project 5, details coming very soon).
  • The introduction to machine learning module is fun, short, and full of quick and easy ML methods!  Enjoy!

Looking ahead

  • For those who are enjoying the class a lot and are thinking about what other AI/ML classes OU offers, the following flowchart may help.  Note that this flowchart may be missing new seminar classes.  For example, I believe Prof Habibi has a new class this spring on autonomous driving which was previously listed as coming soon (dashed lines in the diagram below).
    • AI/ML flowchart for OU classes

Grading

  • The undergraduate project 3 submissions are all graded and I will finish the graduate ones this week!

Hope you have a great week and I’ll see you in slack & office hours!

Week 10

Welcome to week 10 of AI!  Due to travel, this week the announcements are text only but I do have a bonus video for you at the end!

Important Monday news

I’m on the road and the weather has delayed me getting back in time for in-person office hours.  I will be online for office-hours but won’t make it into in-person office hours.  

What you are doing this week

  • This week we move into the second module on machine learning.  We will focus on one of the very common ML methods: decision trees (and their related ensemble methods including random forests).
  • We have 3 more weeks of ML!  Hope you are enjoying it!

Grading

  • My grand plans to finish grading Project 3 are slightly delayed by the bumps in the road, literally.  Hard to finish grading when the laptop is bouncing!  So I am very close to finishing Project 3 but I will finish early this week for anyone who is left!

Fun video 

Where did Dr McGovern go this weekend?  I run my dogs in agility and we used to go to national championships.  This year we did not attend championships as my older dog has cancer and my younger dog wasn’t ready.  My son is a judge in the agility organization that we run in and he was invited to judge in Iowa.  We decided to go up and see him (hence the literal road trip!) and run agility. Below is a bonus video for you to see what we did and I’m relating it to AI:  the specific class that I uploaded is gamblers, which is a game where you have to come up with your own path to collect points.  Sound familiar?  At least there are no moving asteroids!  Enjoy!

Week 11

Welcome to Week 11 of AI!  You all are doing so well and I’m proud of all your progress and projects and how much you are learning!

What you are doing this week

  • This week we move into our third module on ML:  This one is on neural networks and deep learning.  There are TWO classes at OU CS that cover these topics in more detail (Advanced Machine Learning and Artificial Neural Networks and Evolution, see the flow chart above for more information).  Since this class is an introductory class, we only spend a week on the topic just to get you the flavor of it. 

project 5

  • Project 5 is now available on the class webpage – this is the project that focuses on learning!  There is a deadline for it at the end of this week so please go look at it and talk to your partner and get going on your proposal!
  • I worked on all of the remaining projects and modules this weekend and ran out of energy to film all of the videos for project 5.  I will get those filmed and released and added to the project webpage Monday (I write this announcement on late Sunday night to go out Monday morning).

Looking ahead

  • All of your remaining modules and projects are released, with the exception of the project 5 videos.  Module 10 is your final course module and project 6 will be the final project for the class!  Hope you enjoy them!!
  • I’ll work on project 4 grading as you turn them in this week!

Have fun and see you in slack & office hours!

Week 12

Welcome to week 12!  We are almost to the end of the semester and I hope you can see the light at the end of the tunnel!

What you are doing this week

  • This week is our final module in machine learning!  This week we study reinforcement learning, which is a method that many of you decided would be good for project 5 (which I agree).  I think you will enjoy the quick overview!  

project 5

  • I am reviewing your proposals several times a day – please look at your feedback.  Until you receive a grade for it, the proposal is not approved. I want to make sure you all propose feasible projects as I do not want to see you get stuck at the last minute!  Please look at your feedback and respond either in comments, slack, or with an adjusted proposal.

Looking ahead

  • I’ll work on project 4 grading this week also but project 5 proposals will be the first priority.  I will aim to have project 4 done by the end of the weekend.

Have fun and see you in slack & office hours!

 

Week 13

Welcome to week 13!  This is our last week before you get a whole week off for Thanksgiving (I do have a Thanksgiving extra credit assignment but it should be fun and easy and it is 100% optional!!)

What you are doing this week

  • This week we start our last module:  AI & ethics.  This module will last 3 weeks, not including the week off for Thanksgiving.  It should be fun and you will learn a lot about how to ensure that the AI we are developing is not creating harmful outcomes.
  • Note that I added everyone to a new channel in slack called #coded-bias and posted the discussion questions there!

project 5

  • 6 of you made proposals that were not viable and never replied to feedback.  Please go adjust them or else your projects will be very frustrating for you to complete!

Grading

  • Project 4 grading is done for undergraduates and I am continuing the graduate grading!

Have fun and see you in slack & office hours!

Thanksgiving week

Happy Thanksgiving week! You have the week off this week!  There is one extra-credit available if you want but it is 100% optional!  If you engage your friends or family over break in a discussion about AI & ethics, you can get the bonus.  Enjoy your holiday, however you celebrate and see you back in a week!

Week 14

Welcome back from Thanksgiving!  I hope you had a relaxing break and truly got to take some time off!

What you are doing this week

  • We are down to the last 2 weeks of class!  This week you will focus on finishing project 5 and working on the AI & ethics module.  Next week is the project 6 deadline.  Remember it is NOT coding, just creative writing!   

project 5

  • Several of you seem to think that you can use code from the net or existing packages for this project.  Please re-read the rules and realize that you MUST write your own learning code or it will be considered academic misconduct.

Grading

  • I will aim to grade project 5 as they get turned in as I know many of you are trying to compute your final grades.  I will also aim to grade project 6 quickly next week.

Have fun and see you in slack & office hours!

Week 15

Welcome to your final week of AI!  Since the class is online, we have no finals and thus everything finishes this week!

What you are doing this week

  • This week you are finishing Project 5 (it was due Friday but I know some of you are using the 3 days late)
  • You are also finishing Project 6.  Keep in mind that you can NOT submit this one late due to OU rules.  Everything for this class is due by Friday!
  • You have a few items left in the AI & ethics module but I kept it light this week since it is the last week and you are focusing on Project 6

Grading

  • I will work to grade as things are turned in.  I tried to grade Project 5 this weekend but I was out of town and canvas refused to load for me over the cell connection.  I will work to get it graded as quickly as possible this week.

Student Experience surveys

  • This is the first year of OU using the new Student Experience Surveys for all classes.  Please fill them out and let me know your feedback on the class.  I’ve worked hard to make the class accessible and inclusive for all and hopefully have succeeded.  

Bonus video

  • Since you all enjoyed our last dog show bonus video and a discussion of how it relates to AI, I am sharing this fun one from this weekend.  We did a sport called Barn Hunt, where we hunt for rats hidden in tubes in a course full of hay.  It is a multi-agent cooperative team event with a human and a dog (well, you could argue the rats are also autonomous agents!).  You have to clear the whole course, go through a tunnel, climb on a bale of hay, and find all the rats!  It is a hard search task and not one well suited to traditional search methods we have covered this semester.  However, it is a perfect reinforcement learning problem!  Enjoy a bonus video of Arwen searching for rats in a game called Crazy 8s.

I’m Proud of you!

Have an awesome last week of classes!!  I hope you are proud of all that you have accomplished this semester!  The world is not back to “normal” as there are still many stresses on our lives and juggling them with an online class is tricky.  You should be rightfully proud of making it this far!  Give yourself a kudos!