So in this video I am going to talk a little bit about the types of assignments
and the kinds of materials you might use to complete this course.
So with regards to assignments
there's a couple of different types of assignments in this class.
There's the quizzes which are interspersed throughout the units.
They are typically two or three questions just kind of a little bit of a checkup to
make sure that you are paying attention and you got the basic concepts from
the previous videos and things along those lines. I'm going to create them
roughly one every subunit but you know there might be some subunits,
like this one actually, that don't have them in them.
On the other hand we might have some other types of assignments that fill their place
which we'll talk about. Then there's also the tests. The tests appear at the end of every unit.
They are longer than the quizzes.
And both the quizzes and the tests may require a little bit of model running or programming, especially as we get to the later sections of the course.
Early on obviously those focus on conceptual questions.
They may require to do a little bit of work in order to successfully complete those assignments.
Finally and probably in one case I think most importantly is the final project.
And this will be a project that you will be working on throughout the entire course and it is due at the end.
In fact, I want you start right now.
I want you to think a little bit about a particular phenomenon of interest to you that you would like t study through the use of agent-based modeling.
Now, you may change your mind a couple of times I don't want you necessarily to stick to the one you are thinking of right now.
But you know, as you learn more and more you may figure it out.
And along the way I am going to have what I call checkpoints.
These are different points we are going to have something concretely for you to think about, for you to develop for you to kind of help construct that model.
And as a result the project will be developed over the entire course and due near the end of the course.
So, to help you out with this, of course, we have a different set of software that we are going to use throughout this course.
First, this software is something, you have already probably taken a look at. It is something that we talked about in the first subunit, which is NetLogo. Right?
NetLogo is a freely available open source agent-based modeling toolkit developed by Uri Wilensky.
And we are going to talk a little bit more about where it comes from and why it is important in the next units coming up.
But essentially, if you have not done so already, I highly recommend that you go to the NetLogo website, go through the tutorials, download the software, of course install it on your machines.
Because we will be going to use it pretty heavily throughout this course.
And NetLogo is available on any platform: it is on PCs, on Macs, on Linux.
So you can get it working on just about every environment.
It is going to look pretty much the same, too, as well. They have done a very consistent job on it.
In addition to that, we will also being using just a little bit a package called R.
R is a statistical software package.
Primarily my goal there is to introduce you to how to take data you have created from your models in NetLogo, import it to R and do some basic statistical analysis there.
Now, this is not an R course, right? This is much more of an agent-based modeling course.
So I am not going into a lot of detail about how to actually analyze the data once you have it in R.
I do want you to see, how you can bring it in and work on it.
You could, of course, use other agent-based modeling languages. You could also use other statistical software packages to complete this course.
But these are the two we are going to use throughout the course and that we are going to use for examples during the course.
So, probably, if you want to stick to what we are doing, it is probably best to use these two pieces of software.
In addition to the software that we will be using throughout this course, I highly recommend picking up a copy of "An introduction to agent-based modeling" written by me and Uri Wilensky, who is the lead author on this textbook.
This textbook is available both at MIT press and Amazon. And I have the link right here for the MIT press website about it.
The book is in many ways a complement to this online course
in order to be able to go into a lot more detail and provide you with a lot more interesting insight into agent-based modeling that we will not all be able to do during these short video lectures.
[In addition to] Where they purchase the book you can also find some more information about the book at http://www.intro-to-abm.com/.
That is where Uri and I post additional materials we might have for the book, as well as a note saying small typos or things like that, we will post any corrections there as well.
And we also put any additional information about the book available there.
So, I highly recommend picking up a copy. You definitely don't need it to complete this course anyway, but it will be very much an aid to the course as you go through it.
So, this section brings me to your first assignment which is just not one of those little quick multiple-choice quizzes.
Basically, I want to know who you are. I want to get into understanding why you are taking this course, what your interests are in, whether or not you consider yourself to be a computer programmer, an expert in modeling or anything along those lines.
So right now, on the next segment, we will have a link to a participant poll, where you can help us understand a little bit better about who you are.
Now, this is different from the survey that Complexity Explorer will be sending out, where they try and get and idea of what the various people who are attending the course are.
This one is tailored specifically to this course and will help us understand your interests and your angles for this.
So, go ahead, go ahead and complete it right now.
And in the next subunit, we will start to dive into what agent-based modeling is all about.