Welcome to an introduction to Agent-Based Modelling.
I'm Bill Rand and I'll be your instructor for this course.
I am a Assistant Professor of Business Management
at the College of Management at Carolina State University,
and I also have a training in Computer Science.
And in this course, we're going to be talking about why
agent-based modelling is useful,
what you can use it for,
how you can understand it,
how you can build models, how you can understand models
other people have built, how to analyse those models,
and how to use those models in advanced ways to really start to
understand problems that you might see around you.
Now, throughout this course, we're going to talk about technical details,
but we're not going to require you to know anything about computer programming
or computer modelling, going into the course.
But before we get into all those details, I want to start with kind of a brief video
a brief discussion, that I usually start almost all of my agent-based modelling classes with.
So, what you're seeing in front of you
is a set of birds that often flock together in very interesting ways.
And they do this as they move through space,
without really coordination, without really kind of any centralized plan
of where they should go or how they should move,
but the patterns that they generate are quite ornate, and quite beautiful,
and they have a certain regularity to them,
if you observe them over time.
A certain pattern of behavior that you see throughout them.
And a lot of what we're going to talk about,
is how to go from individual level rules of behavior
to these aggregate beautiful emergent patterns that we see around us.
And that's what agent-based modelling, in many ways,
was designed to do. So how can individuals,
who are behaving on their own, come together to create these vast patterns
of behavior that we see around us?
And more importantly, or I should say, in addition,
how do those patterns of behavior then feedback to affect those same indivduals
trying to make decisions?
Now, let's try and work backwards from this to begin with.
So, I'm going to bring up now, a computer model that was created to kind of represent
the patterns in these birds, that we see around us.
And in this computer model, as you might see in front of you,
birds often behave in very similar ways to the ways of the actual birds that we saw
in real life. Now, they're not quite the same, there are some differences,
this is the two-dimensional model, as opposed to a three-dimensional model,
and there are other reasons why there is a difference in the ways that they behave,
but in other ways, they are quite similar.
Now, I'm going to start and stop the model several times,
And you see that you start with a random distribution of birds,
what we're going to later call "agents" throughout this course,
and these birds move and interact, but slowly, they coalesce,
and we're going to speed the model up a little bit and slow it down a little bit,
and you can see how they might interact with each other.
Now, if you've never seen this model before,
I encourage you to kind of go back and look at the model several times.
And if you want, this model is actually available in NetLogo,
in the language that we'll be using throughout this course,
and it's called the Flocking Model in NetLogo.
If you go and open the NetLogo model,
and you go to Files > Models Library > Biology,
and then click on the Flocking Model,
you can see the model for yourself.
And what I want you to do, is I want to have you hit "setup" and "go",
several times, without really looking anything else in the model,
really exploring the model,
and I want you to try and start to infer the rules of behavior
of the birds in this model.
Now, I'll give you some hints,
there are only three rules,
and they're very simple. Okay?
The colors of the birds have nothing to do with the rules.
The colors are just there to differentiate one bird from the other,
so they don't appear to all be the same exact bird,
in the original,
and all the birds act in exactly the same set of rules,
there is no difference between the set of rules that the birds behave. Okay?
So, at this point, I'm going to stop this video,
and I want you to try and see if you can write out,
on maybe a scratch paper or anything that you might have around,
the three set of rules that exist with our system.
And when we come back, I'm going to explain to you what the three rules are,
and why they're a great way to get an introduction to agent-based modelling.