Computer Simulation

Wikipedia

Number of words 2220
Computer science content low
Math content medium
English language complexity medium

Sub-areas covered

Learning objectives

Keywords

mathematical model (model matematyczny)
an abstract model that uses mathematical language to describe a system
Computer Generated Imagery (CGI)
an application of the field of computer graphics (or more specifically, 3D computer graphics) to special effects in films, television programs, commercials, simulation
differential equations (równania różniczkowe)
a mathematical equation for an unknown function of one or several variables that relates the values of the function itself and of its derivatives
gamut (gamut)
a certain complete subset of colours
Monte Carlo method (metoda Monte Carlo)
a computational algorithm which relies on repeated random sampling to compute its results
stochastic (stochastyczny)
describes a process whose behavior is non-deterministic in that the next state of the environment is not fully determined by the previous state of the environment
discrete (dyskretny)
not supporting or requiring the notion of continuity; discrete objects are countable sets such as integers

Summary

The article presents a general view of computer simulations. It explains what a computer simulation is and the differences between simulation and modelling. It provides a brief overview of the history of computer simulation and divides computer simulation into specific types: stochastic and deterministic and continuous and discrete, giving examples of each kind. It sets out the advantages of CGI simulations and describes the impact of simulations on present-day science. The final part of the article lists practical contexts for computer simulation which are important in everyday life.

Artykuł prezentuje ogólną ideę symulacji komputerowych. Wyjaśnia, co nazywamy symulacją komputerową oraz jaka jest różnica między symulacją a modelowaniem. Krótko opowiada o historii symulacji komputerowych, oraz prezentuje różne typy symulacji: stochastyczne i deterministyczne, ciągłe i dyskretne wraz z przykładami. Przedstawia zalety symulacji typu CGI oraz wpływ symulacji na współczesną naukę. Na końcu możemy się dowiedzieć, gdzie spotykamy się z symulacją w naszym codzien- nym życiu.

Pre-reading questions

  1. How can we solve problems in cases where physical models are too complex or expensive to build?
  2. Name some problems which can be solved using computer simulation?