Research Project: MoSiLLDe

Modeling and Simulation of Linked Lives in Demography


     Runtime:

     Project coordination:

     Scientific
     Staff:

     Student staff:

     Cooperation partners:

     Source of funding:

Nov 01 2014 until Dec 31 2017

Prof. Dr. Adelinde M. Uhrmacher

M.Sc. Oliver Reinhardt • Dipl.-Inf. Alexander Steiniger (until 31.08.2015) • M.Sc. Tom Warnke

Sebastian Plath • Lars Roesicke • David Oliver Taube

Max Planck Institute for Demographic Research Rostock
Prof. Dr. Frans Willekens • Dr. Anna Klabunde • Dr. Sabine Zinn

DFG  (DFG GEPRIS Link)

Abstract

 
In this project we will develop a new domain specific modeling language, efficient execution algorithms, bring together data-driven and hypothesis driven model development and, together with our cooperation partners from the Max Planck Institute for Demography Rostock, we will develop models to analyze migration patterns between Africa and Europe.

Continuous-time microsimulation is an important method for predicting demographic changes in the next decades. However, these modeling and simulation studies face various challenges. One is to integrate in an adequate manner dynamics at different organizational levels, i.e. at micro level (e.g., individuals), and at macro level (e.g., population), and linking those dynamics in continuous time and discrete space. During the last decade, demography has started moving from data- to hypothesis-driven development of individual-based models. This has an impact on processes and methods used for validating these models. The project aims at addressing chal- lenges of continuous time micro simulation in demography and will provide contributions in the area of (simulation) modeling languages, efficient simulation, and guidance and documentation of simulation studies.

  • A modeling language shall be developed that allows a succinct modeling of life courses of individuals and populations, and link those life courses in continuous time and discrete space. It will be realized within the modeling and simulation framework James II.
  • Due to enabling a compact description of an individuals life course and decisions over time and space and the demand to simulate millions of individuals, efficient execution algorithms for the modeling language are needed. To address the need for an efficient simulation a variety of approaches to speed up model execution shall be explored, i.e., from simulator configuration on demand, approximative schemes, to parallel algorithms.
  • The modeling language shall allow to define hypotheses about what determines the life course of individuals in a flexible manner. To validate these hypotheses experiments different from the typical data based ones are needed. Based on the portfolio of methods provided in James II workflows shall be defined that support data- and hypothesis-driven modeling and experimentation.
  • A set of smaller case studies shall be developed to evaluate the methods. In addition, in cooperation with partners from demography, the modeling language will be used to describe, explain and predict international migration using individual-level data.