Simulation: testing a model — Computing, 11–13
A simulation uses a simplified version of a real situation so you can try ideas safely and cheaply.
The big idea
A simulation is a program that imitates how a real or imagined system might behave. It keeps the important rules and leaves out details that do not matter for the question. You can change its starting conditions, run it, and see what could happen.
The problem it solves
Some experiments are too dangerous, expensive, slow, or large to perform in the real world. You cannot test every design by crashing a real plane or wait centuries to watch a climate change. A simulation lets you compare possibilities before making a real decision, while remembering that its model is only an approximation.
A worked example
Suppose a model asks whether a pond can support 20 fish. Step 1: start with 20 fish and 100 units of food. Step 2: each month, fish eat 3 units and 2 new fish are born. Step 3: after one month, food is 97 and fish are 22. Repeat the rules to spot when food runs out, then change a rule and compare.
A tempting mistake
It is easy to treat a simulation’s result as a prediction guaranteed to come true. But the result depends on the rules, starting values, and missing details in the model. A useful simulation is evidence for comparing choices, not a crystal ball; test it against real observations when possible.
Where you meet it
You meet simulations in weather forecasts, driving practice, city traffic planning, science games, and training for emergencies. A game about building a town is also a simulation when its rules model money, space, and resources. Its world is not the real world, but the model can help you explore trade-offs.
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