Social systems and their simulations

Lecturer:

Tutor:

Supervisor:

Department of Mathematics

Synopsis:

The course is devoted to the issue of social systems modeling. That includes stochastic methods and methods of statistical physics for description and analytical solution of social interaction systems, implementation of particular models and comparison of the computer simulations results with the empirical data.

Requirements:

Basic course in Probability and mathematical statistics, statiscal physics, analysis of chaotic systems and programing in MATLAB (in the extent of the courses 01PRST, 01SM, 02TSFA, 01CHAOS, 18MTL held at the FNSPE CTU in Prague).

Syllabus of lectures:

Interdisciplinary aspects of quantitative sociodynamics, basic features of social interactions a their quantification, basic terminology, social phenomena, psychological aspects of the decision process, stochastic methods for social-interaction processes, non-linear dynamics of social flow, elementary master equation, Boltzman-like equation for social system, master equation in configuration space, Fokker-Planck equation, Langevin equation and non-linear dynamics of social system, quantitative models of social processes, social-force-based models, decision theoretical specification of the transition rates, opinion formation models, evolutionary game theory, determination of the model parameters from empirical data.

Syllabus of tutorials:

1. Computer simulation of particular models of social system, 2. The steady-state solution by means of Fokker-Planck and Langevin equation, 3. Gaining and processing empirical data.

Study Objective:

Mathematical description of social-interaction system, Review of models used for simulating social systems, application of stochastic methods and methods of statistical physics for their analytical description (Boltzmann-like, Fokker-Planck, Langevin equation). Skills: Computer implementation of the model, processing and comparing of simulation results with empirical data.

Study materials:

Key references:

[1] D. Helbing, Quantitative Sociodynamics: Stochastic Methods and Models of Social Interaction Processes, Kluwer Academic, Dordrecht, (1995)

[2] W. Weidlich, Sociodynamics - a systematic approach to mathematical modelling in the social sciences, CRC Press, 2000

Recommended references:

[3] D. Helbing, Traffic and related self-driven many-particle systems, Rev. Mod. Phys 73 (2001), 1067

Media and tools: Computer training room with Windows/Linux and programming languages C, MATLAB.

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: