Agent-based modelling for social research- Block 1: Introduction to Modelling, Introduction to Agent-based models, Time in Agent-based models
Presenter(s): Jakub Bijak, André Grow, Martin Hinsch, Oliver Reinhardt, Toby Prike
Agent Based Modelling for Social Research- Introduction
In this video, Professor Jakub Bijack introduces the online materials for this short course on Agent-Based Modelling for social research, outlining the share a novel approach from building, validating and analysing agent-based simulation models, developed as a part of a four-year programme based on agent-based population studies funded by the European Research Council.
Introduction to Modelling Part 1
In this video, Dr Martin Hinsch gives a brief general introduction to modelling, first looking at predictive models and then explanatory models.
Introduction to Modelling Part 2
In this video, Dr Martin Hunsch focuses on modelling, talking about complexity, chaos, criticality and emergence.
Introduction to ABM
In this video, Dr André Grow introduces the basics of agent-based modelling, presenting examples from his own work to demonstrate how the method works and what kind of questions you can address.
Time in Agent-based models
In this video, Oliver Reinhardt introduces you to two different ways to advance time in an agent-based simulation, identifying some of the inherent problems of time-stepped simulations and how to avoid them with discrete event simulation.
About the author
Jakub Bijak is Professor of Social Demography and currently a Joint Head of Department of Social Statistics and Demography at the University of Southampton, UK. At present, he leads an ERC funded project on Bayesian Agent-Based Population Studies and a H2020 project QuantMig: Quantifying Migration Scenarios for Better Policy. His email is j.bijak@soton.ac.uk.
André Grow is Research Scientist and a Research Area Chair in the Laboratory of Digital and Computational Demography at the Max Planck Institute for Demographic Research in Rostock, Germany. His interests include agent-based computational modelling, family sociology, social stratification, and digital demography. His email address is grow@demogr.mpg.de.
Martin Hinsch is a Research Fellow in the Department of Social Statistics and Demography at the University of Southampton. He is interested in emergent structures and complex systems and has done research in theoretical biology, bioinformatics, machine learning, epidemiology and swarm robotics. His email address is hinsch.martin@gmail.com.
Oliver Reinhardt is a Ph.D. student in the Modeling and Simulation Group at the University of Rostock. He holds an MSc in Computer Science from the University of Rostock. In his research, he is concerned with domain-specific modelling languages and the methodology of agent-based simulation. His email address is oliver.reinhardt@uni-rostock.de.
- Published on: 27 April 2021
- Event hosted by: University of Southampton
- Keywords: Agent-based modelling | Computational social science | Model analysis and experiments | Model documentation | Modelling and simulation | Modelling languages |
- To cite this resource:
Jakub Bijak, André Grow, Martin Hinsch, Oliver Reinhardt, Toby Prike. (2021). Agent-based modelling for social research- Block 1: Introduction to Modelling, Introduction to Agent-based models, Time in Agent-based models. National Centre for Research Methods online learning resource. Available at https://www.ncrm.ac.uk/resources/online/all/?id=20766 [accessed: 20 April 2024]
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