The science of complex systems is the science of systems that are highly interconnected, have behaviors that are sensitive to initial conditions, and have outcomes that are hard to predict. Some examples of complex systems are cells, brains, ecologies, economies, and societies.

Agent-based modeling is a way of studying complex systems. An agent-based model consists of a virtual world filled with agents. Agents are like creatures that follow simple rules. They can represent any kind of individual: people, cars, atoms, rabbits, cells etc. Complex systems can be modeled by giving the agents a set of rules for how to behave and interact. The results are often surprising.

Here's an example of an agent-based model of complex system: suppose you had a world consisting of termites, and chips of wood. The termites are the agents in this model. Their rules are as follows:

• Wander around randomly
• If you bump into a wood chip, pick it up
• If you're carrying a wood chip, and you bump into another one, put it down

Given only this set of rules, what would you predict will happen to the wood chips over time?

Click next to test your predictions.