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Scientific Coordination

Dr.
Sebastian E. Wenz
Tel: +49 221 47694-159

Administrative Coordination

Angelika Ruf
Tel: +49 221 47694-162

Week 1: Agent-based Modelling in the Social Sciences

About
Location:
Online via Zoom
 
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 500 €
Academics: 750 €
Commercial: 1500 €
 
Keywords
Additional links
Lecturer(s): Prof. Dr. Andreas Flache, Carlos de Matos Fernandes, Tanzhe Tang

About the lecturer - Prof. Dr. Andreas Flache

About the lecturer - Carlos de Matos Fernandes

About the lecturer - Tanzhe Tang

Course description

Agent-based computational modeling (ABCM, or often just ABM) increasingly attracts social scientists as a tool for unravelling the complex dynamics which often underlie puzzling social phenomena such as segregation, cultural diversity, opinion polarization, or collective action. ABCM is an approach for theory elaboration that combines analytic precision, ability to capture complex micro-macro interactions in a computational model, and flexibility to accommodate empirically realistic assumptions. This course gives an introduction to ABCM for social scientists, focusing on its use for theory building and on best practices for systematic experimentation and analysis of models. In tutorials accompanying the lectures, participants get a “hands-on” introduction to software tools specifically designed for ABCM of complex (social) dynamics. Participants learn to build ABCM from scratch for a range of core domains in the social sciences, including segregation, cooperation, cultural diversity, and opinion polarization and how to systematically experiment with these models for gaining a deep understanding of them. Throughout the lectures, “classical” and more recent ABCM will be introduced and explained, while participants learn to work, experiment, and extend these models in tutorial sessions. Participants will specifically work with two software tools: NetLogo, a widely used software and defSim, a new Python-based tool for modelling social influence dynamics.


Target group

Participants will find the course useful if:
  • Master, research-master or PhD-student level in a social science discipline or related disciplines.
  • Affinity with formalizing social-scientific theories


  • Learning objectives

    By the end of the course participants will:
  • Understand the use of ABCM for analysing complex social processes
  • Understand the concept of social complexity and its relation to ABCM
  • Know and understand the substantive problems, theories and classical as well as recent related computational models in a number of core areas of social scientific research (e.g., segregation, diversity, polarization, cooperation)
  • Be able to build ABCM models tackling these phenomena from scratch, using NetLogo or defSim (a tool based on Python)
  • Be able to apply a set of good practices for developing a deep understanding of complex social dynamics through systematic experimentation with ABCM.
  • Be able to reflect upon the strength and pitfalls of ABCM as a tool for theory development in the social sciences
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    Organisational Structure of the Course:
    Course structure: there will be about three hours of classroom instruction and about three hours of hands-on tutorials and exercises per day. The lectures will introduce and explain the theory and methods in ABCM research, substantive problem areas in the social science literature and the specific ABCM and their contribution to scientific insight per domain. In the tutorials, participants are expected to work individually or in small groups on building from scratch, applying and extending ABCM for specific research questions discussed in the lectures. They will work based on template models and instructional material provided by the lecturers. Tutors experienced with the software tools (NetLogo, defSim) and sample models will provide hands-on guidance and supervision.
     
    Depending on interest of the students, some time can be made available for consultation on students' own ABCM projects.


    Prerequisites

  • Interest in and affinity with formal (computational, mathematical) modelling of social processes
  • Master, research-master, PhD-student or postdoctoral level in a social science discipline or related disciplines
  • No specific prior programming experience required
  • Affinity with formalizing social-scientific theories is desirable
  •  
     
    Software requirements:
    NetLogo, most recent version, freely available at https://ccl.northwestern.edu/netlogo/download.shtml. Participants should install NetLogo on their machines prior to the workshop.
    defSim (open source, based on Python, can be used with google colab, colab.research.google.com/). See further https://defsim.github.io/defSim/. No pre-installation needed.