MSC-How Computer Models and Simulations Work Lesson

How Computer Models and Simulations Work

To gain a better understanding of how computer modeling works, let's think about baking a cake that has 20 ingredients. If you want to know how each ingredient contributes to the outcome of the cake, one option would be to bake 20 cakes and leave out a different ingredient each time. Such an approach would be extremely time-consuming. Alternatively, you could enter all 20 ingredients into a computer model, explaining to the computer what each ingredient does and how it interacts with other ingredients. You could then run a simulation in which a different ingredient is left out each time. In a matter of seconds, the computer could tell you how each of the 20 cakes would likely turn out if baked in real life.

Let's say you now want to know how changing the amount of each ingredient will affect the cake. In your computer model, you could adjust the amounts of each of the 20 ingredients any number of times until the outcome of your simulation is a cake that suits your needs (e.g. fluffy, sticky, soft, hard, etc.).

In real life, you would need to bake 190 cakes to find out the results of changing any 2 ingredients; 1,140 cakes to find the results of changing any 3 ingredients; and 4,845 cakes to find the results of changing any 4 ingredients.

Computer models can be created by using spreadsheet programs or other computer simulation software programs.

Spreadsheet Programs

Spreadsheets can be used in business to model and display financial details and answer "What if" questions.

The spreadsheet can be used to predict future profits or losses for a business. For example, "What if we decrease the workforce by 15% Will our profits increase or decrease?" The managers of the business can then analyze the answers to these questions and make decisions based on them.

Spreadsheets are used for manipulating numeric data stored in rows and columns. Mathematical formulas are applied to the model and observe the relationship between the data. Graphs and charts are created for visual interpretation of the data.  

Simulation Software Types

Simulation software programs are used to observe an operation through simulation without actually performing that operation. There are many different types of computer simulation programs based on different criteria.

Stochastic Simulations

Models that rely on random numbers are called stochastic simulations.    

Models that rely on random numbers use the Monte Carlo technique. Monte Carlo technique requires many runs because the result from each run depends on the random values drawn for various input, initial, and internal conditions.  

Deterministic Simulation

Deterministic simulations contain no random variables and no degree of randomness. These simulations have known inputs and the results are the same no matter how many times you re-calculate it. The system is perfectly understood and it is possible to predict precisely what will happen. These models are usually developed by statistical techniques and equations. An example would be the amount of interest from a principal amount and interest rate.

Discrete Event Simulation

A discrete event simulation represents an event at an instance in time. The points in time are ones at which the change in the event occurs. Discrete simulation relies upon countable occurrences like the number of individuals in a group or the number of darts thrown.

Continuous Simulation

In a continuous simulation, variables change in a continuous way. Continuous simulation is found inside Wii stations, commercial flight simulators, and jet plane autopilots.    

Agent-Based Simulation

Agent Based simulations use artificial agents and place them in a computer simulated world to observe the behaviors of the agents.

The agents exist in an environment defined by the model. The agents interact according to a set of protocols defined in the simulation to represent how the individuals might interact in the real world. Each agent can recognize and reason about the traits of other agents that it comes into contact with in the simulation. The agents are autonomous, that is they have their own reasoning and decision-making approaches. Each agent has a memory, or history of past state, and learns and adapts from experience. It changes its behaviors in response to new knowledge and experiences.

Spreadsheets and Simulations for Modeling Activity

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