so picking up on our list of aspects of
a complex system that might indicate
that you want to use agent based
modeling to understand that system
another key element that we often see is
Rich environments uh so what I mean by
that is that the environment is uh has a
lot of properties a lot of uh potential
possibilities of inter acting with the
agents or maybe defines really the way
the agents interact in the first place
um and within agent-based modeling the
environment that the agents interact in
can be extremely rich to get an example
right as two examples are social
networks and geographical systems so
social networks we've seen a little bit
in the past but essentially we can
describe all the ways that agent might
interact with another agent VI have a
set of networks and links that connect
one that agent to those other agents all
right another environment that might be
very rich is a geographical system or a
geographic information system if you're
pulling the data directly from such a
device right and in this case what we're
talking about is the agents might
actually physically be located in your
model in an actual real geography and
that geography may contain a number of
elements that affect agent decisions
they can be anything from elevation to
whether or not there's a transportation
Network nearby to the school district
that they're inhabiting uh to a number
of other aspects right and agent-based
modeling really allows you to decouple
the agent itself from that physical
system and allow you to work uh to
examine how those systems move around or
interact with each other um the
environment can in fact even have its
own agent Like rules right you could
have a farm type environment in which
the farm actually grows and things and
the crops grow and the agent comes along
and cuts the props and stuff along those
lines in which case the the environment
itself might have prototype agent roles
it's just they can't move around right
in many ways um the reason why this is
very useful is that agent based modeling
is a model of process which we will talk
about in just a second um whereas
environmental system environmental data
is often a model of pattern and agbas
modeling provides a nice framework we
could Mel together these models of
process with this model of pattern in
order to understand what's going
on so almost all agent-based models in
fact feature time and this is because
agent-based modeling is a model process
we're talking about how agents change
over time how they interact with other
agents how they look at um the world
around them and how they make decisions
based upon their past steps right in
fact most of the major Agia based moding
platforms out there even go so far as to
define a temporal unit often referred to
as a TI tick which we'll see later on or
a Time Step In some cases but usually a
tick um and that tick indicates one
discrete unit of time has passed right
um and that's that's very much a core
concept within a lot of Age based models
and in fact I would call it a nearly
necessary condition of applying
age-based model there are exceptions so
for instance I've seen some examples of
solving very complex equilibrium
problems essentially using the ebased
model to solve kind of a game theoretic
problem where you're trying to explore
what the different possib actions an
agent might take but even in those cases
there really is kind of a notion of time
it's the notion of time where they're
trying to see if I took this action what
could possibly happen so the agents
themselves are kind of exploring time in
that
space as opposed to time which is a
necessary condition of most Age based
modeling approaches adaptation is almost
a sufficient condition if the agents you
want to EXP explore feature adaptation
then there is very few other methods by
which you can understand that system
except through some form of agent-based
modeling now let's be precise about what
adaptation means in this case I don't
mean that necessarily that the agent
takes different actions over time I mean
that the agent takes different actions
over time even when presented with the
exact same set of the world state of the
world that they had seen in the past
past and that its reason for taking that
new action is due to some experience it
has in the past in other words
adaptation is when an action's a agent's
actions are contingent upon their past
history within that system an agent in
this case an agent in this case may in
fact take different actions depending
upon its own past experience in order to
really model adaptation within an agent
you need to have a history that is f
coming along with every agent as well as
a rule that tells how to act upon that
history in the context of future events
that is approach that is previously seen
within the history very few other
modeling approaches besides ABM feature
adaptive individuals and therefore this
is usually a sufficient uh condition for
applying AG of based modeling so now
that we've gone through all of the six
conditions it's useful to look back at
the overall list I often suggest doing
this before deciding whether or not you
want to use AGP moding to understand a
problem the way I recommend doing this
is you take these Force four um
indicators medium numbers heterogenity
complex but local interactions and Rich
environments the more of these that the
system that you want to study possesses
the more likely it is that AG based
modeling is going to be useful to you
and if it violates too many of these in
other words if the system is homogeneous
it has Global interactions and has large
numbers right um then you might want to
consider an alternative approach on the
other hand you should also check to make
sure does the system feature time if it
doesn't then you have to have a very
good reason to justify the use AG use of
agent based modeling and finally if the
system contains adaptive agents there
are very few other approaches out there
besides agent based modeling uh that
will be useful for understanding that
system so given all this I often
recommend that when you start to think
about whether or not I'm going to study
this uh system using an agent based
modeling approach pull out this
checklist take a look at it and see
whether or not it meets the criteria
that we've discussed