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.