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Simulation as a Tool to Model Stochastic Processes in Complex Systems

  • Klaus G. Troitzsch
Part of the Advances in Computational Economics book series (AICE, volume 11)

Abstract

In this paper we describe the use of computer simulation in the social sciences and economics. These sciences deal with complex systems in which large numbers of components influence each other in a large variety of ways, and some of these influences are stochastic or can best be modeled as stochastic. After a short overview of the history of simulation in the social sciences and economics, two types of simulation are characterized, simulation as numerical treatment of mathematical models otherwise unsolvable, and computer simulation in its own right, where real world entities are mapped on programming language objects. We describe the steps in which modeling and simulation usually proceed, and then turn to a discussion of different purposes of simulation, using a number of simulation examples which at the same time serve to give a first impression of different simulation techniques, to show qualitative and quantitative aspects of simulation and to introduce problems which arise in estimation,

Keywords

Cellular Automaton Target System Numerical Treatment Symbol System Cigarette Brand 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Klaus G. Troitzsch

There are no affiliations available

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