• Tuesday and Friday, 10:15-11:45
  • MK 1101 (Tuesday), MG 410 (Friday)

First Session

  • 08.11.2005


  • Michael Möhring, Thomas Pitz, Torsten Chmura

Intended Audience

  • Bachelor of Science in Information Management: 3rd year
  • Computer Science: 3rd or 4th year


Presentation of a simulation model or a simulation tool

Related Event



The aim of this module is a broad introduction into all approaches to simulation in the social sciences. Being not only a ZUMA workshop, but also part of the computer science and information management programmes of the Computer Science Faculty of Koblenz-Landau University (KLU), this module is designed for students in their 5th or 7th semester. It covers the basics of modelling and simulation in the social sciences from different points of view (mathematics, computer science, philosophy of science) and of seven different approaches to computer simulation in the social sciences.

By the end of this module, a student should understand

  • what simulation is good for in the social sciences and which steps should be taken to arrive at a useful computer simulation and he or she should know
  • which approaches have been followed by social scientist in the past decades, what the aims of these approaches were and which advantages and shortcomings these approaches have.

Moreover, students should be able to make use of a number of different simulation tools and have gained some experience in designing their own models.


  1. Overview/Simulation and Social Science — history, taxonomy, motives, simulation from a philosophy of science point of view (08.11.2005)
  2. Simulation as a Method — logic of simulation, stages of simulation-based research (15/11/2005)
  3. Systems Dynamics and World Models — classical approaches to macro simulation, differential equations, macro simulation tools, qualitative simulation (18-22/11/2005)
  4. Microanalytical Simulation Models — classical approaches to micro simulation, tax and pension models, recent tools (25-29/11/2005)
  5. Queuing Models — discrete event simulation, business process modeling, tools (02/12/2005)
  6. Multilevel Modelling — modelling global interactions between populations, groups and individuals, stochastic processes, synergetics (06-09/12/2005)
  7. Cellular Automata — game theory, modelling local interactions in large populations of identical actors (13-16-20/12/2005)
  8. Distributed Artificial Intelligence Models — agent based social simulation (10-13/01/2006)
  9. Learning and Evolutionary Models — artificial neural networks, genetic algorithms (17/01/2006)
  10. More models (depending on the time left between the lecture part and the lab, discussion and presentation part of the course) (20-31/01/2006)


Students will present models from various available toolboxes. Details will be given during chapters 3 though 9 of the lecture part (03-21/02/2006)

Basic Reading

Nigel Gilbert and Klaus G. Troitzsch: Simulation for the Social Scientist 1999. Open University Press. London; second edition 2005