Complexicon: Agent-Based Modeling

Agent-based modeling is a type of modeling in which

the action and interactions of autonomous agents.

Both with each other and the environment

are explicitly modeled in computer program.

The agents can be nearly anything,

animals, people, cities, nations.

Usually the agents follow simple rules

and are influenced by the other agents

and their immediate surroundings.

Let’s use an example to show what this means.

In this model there is some fish,

the agents that follow one simple rule,

swim straight.

When a fish exits on one side it,

re-enters on the opposite side,

not very excited right.

To make things more interesting,

let’s add a second rule.

Occasionally each fish randomly changes its direction

a little bit away from its current direction.

This is more interesting, but still not very exciting.

The fish aren’t interacting with each other.

Adding one final, third rule makes all the difference.

Rather than going more or less in the same direction,

each fish moves in more or less the average direction

of all the fish in its local neighborhood.

This mimics real life, an actual fish

in an actual school can’t see the entire school,

but it can sense the fish closed by.

Agent-based modeling is much more flexible

than other types of modeling

such as equation-based modeling.

With enough rules, almost any behavior can be modeled

in any phenomenon can be observed.

But this flexibility also has its down side.

Agent-based models with too many rules are hard to understand.

If there are twenty rules effecting one agent

how are we to know which rule is felt most strongly.

For example what rules are necessary to observe

a phenomenon such as the schooling of fish

could a simpler model yield schooling.

Nevertheless a well-designed agent-based model

can be very informative.

It can tell us which combinations of behavioral rules

for agents and environmental conditions yield

interesting behavior such as the schooling of fish.

What’s cool about this model

is that the fish actually forms school

based on three simple rules.

They present a different way to understand

how phenomena and patterns can arise

from very simple behavior,

which is a hallmark of complex systems.

Agent-based modeling is foundational to the science

that we do here at the Santa Fe Institute.