MSC- Models and Simulations in Computing Overview

 

Models and Simulations in Computing

A computational model or simulation is a computer program that attempts to imitate a particular system. Computer simulations have become a useful part of demonstrating many natural systems in physics, chemistry and biology, economics, psychology, and social science. They are also used to aid in education and for personal enjoyment. Simulation and Gaming can be done with board games, computer assisted board games, or fully computerized environments.    

In this module, you will explore different types of models and simulations to understand how they are used to generate new knowledge and understand phenomena in the real world. You will also analyze existing models using different scenarios to gain knowledge about the real system.  

Essential Questions

• What is a model?
• What is a simulation?
• How do models and simulations help answer questions about the real world?
• What are different types of models and simulations?
• How does society use models to generate new understanding of knowledge?

Key Terms

model – an abstraction of a real world system.

simulation –the execution of a model, represented by a computer program that gives information about the system being investigated or other phenomena.

phenomena – something that can be observed and studied and that typically are unusual or difficult to understand or explain fully.

scale model - a physical model of a system that might be larger, smaller, or the same size as the system it represents.

stochastic simulations - simulations that operates with variables that can change with certain probability.

Monte Carlo simulation - computational algorithms that rely on repeated random sampling to obtain numerical results.

deterministic simulation - contains no random variables and no degree of randomness.  

continuous simulation - variables change in a continuous way.

agent based models - use artificial agents and place them in a computer simulated world to observe the behaviors of the agents.

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