Glossary

A

Abstraction

Criticality: 3

The process of simplifying complex details to focus on the essential aspects or main idea of a system or problem.

Example:

When you use a map, you're benefiting from abstraction because it removes unnecessary details like individual trees and buildings to show only roads and landmarks.

B

Bias (in simulations)

Criticality: 2

A systematic error or distortion in a simulation's results caused by the creator's choices about what to include or exclude, leading to an inaccurate representation.

Example:

A traffic simulation might have a bias if it only models rush hour traffic and doesn't account for lighter traffic periods, leading to an overestimation of congestion.

O

Oversimplification (in simulations)

Criticality: 2

When a simulation is made too simple, omitting crucial details that are necessary for an accurate or useful representation of the real-world system.

Example:

A simulation of a human heart might suffer from oversimplification if it only models blood flow and ignores the electrical impulses that regulate the heartbeat.

R

Random number generators

Criticality: 2

Algorithms or devices that produce a sequence of numbers that appear to be random, used in simulations to introduce variability and unpredictability.

Example:

In a game simulation of a dice roll, a random number generator would produce a number between 1 and 6 to mimic the unpredictable outcome.

S

Simulation

Criticality: 3

A simplified model of a complex real-world system or event, used to study its behavior without direct interaction.

Example:

A weather simulation might use temperature, pressure, and humidity data to predict if it will rain tomorrow.