# Simulation and Modelling

## Introduction to Simulation and Modelling

• Simulation is a method used to imitate a real-world system or process over time.
• Modelling is the creation of an abstract representation of a system, often in the form of mathematical equations or computational models.
• Simulation modelling is a combination of these two methods, where a model is used to conduct a simulation.
• This can be useful to predict outcomes and discover new insights.

## Uses of Simulation and Modelling

• These techniques have applications in a wide range of areas, such as physics, engineering, economics, medicine, and computer science.
• They can be used to simulate real-world scenarios, such as the spread of a disease or the behaviour of a financial market.
• This can help to analyse and understand complex systems, and to test hypothetical scenarios without the risks associated with real-world experimentation.

## Types of Simulations

• Deterministic simulations provide the same output each time they are run, assuming no changes have been made to the model or initial conditions.
• Probabilistic simulations incorporate elements of chance or randomness into the model, producing different results each time the simulation is run.
• Static simulations model systems at a specific point in time, while dynamic simulations represent systems that change over time.
• Discrete simulations model systems that change at distinct points in time, and continuous simulations represent systems that are changing continuously.

## Modelling Techniques

• Models can be represented in various forms such as mathematical equations, diagrams or computer programs.
• Agent-based modelling involves the creation of individual entities, called agents, each operating independently according to pre-defined rules.
• System dynamics modelling is often used for modelling complex systems, using feedback loops and time delays to represent the behaviour of the system over time.