Agent-Based Modelling for the Social Scientist

Key information

Start date: To be confirmed

Attendance dates:

To be confirmed

Time commitment: 3 days


Stag Hill campus, University of Surrey, Guildford, Surrey GU2 7XH

Contact details:


Simulating social interactions in virtual research labs using agent-based modelling is increasingly allowing researchers to gain new insights into the complex ways that individuals and societies function.

In this course, you will be introduced to foundation theoretical and practical aspects, the process of agent-based modelling, from conceptualising a research question, where to obtain data, operationalisation and formalisation of data, model implementation, and model analysis and interpretation.

In addition to the theoretical content, you will learn NetLogo as a programming language for agent-based models. Through step-by-step lab sessions, you will learn to develop a detailed model of a social phenomenon (e.g. a market, virus spread). You will also learn the major features of programming in NetLogo through practical application. You will acquire basic to intermediate programming skills in NetLogo as well as engaging with the step-by-step development of a model.

This course is offered in collaboration with the Centre for Research in Social Simulation, one of the first research groups to use agent-based modelling in the social sciences.

Learning outcomes

On successful completion of this course, you will be able to:

  • Understand the foundations of simulation modelling in the social sciences (K)
  • Think about a social problem in an agent-based modelling relevant way (C and T)
  • Understand application areas of agent-based modelling (C and K)
  • Understand different implementations of social phenomena e.g. networks, neighbourhoods and social influence (C and K)
  • Conceptualise different kinds of agents e.g. behavioural, reactive and cognitive (C)
  • Program in NetLogo to an intermediate level (K, P and T)
  • Provide a basic model conception, specification, implementation, verification and validation (C and P)


KSubject knowledge
PProfessional/practical skills
TTransferable skills

Course content

  • What is agent-based modelling?
  • Basics of agent-based model implementations
  • Approaches to behaviour rules i.e. game theory, BDI and social psychology
  • Running and analysing experiments
  • Sensitivity analysis and robustness tests
  • Verification and validation
  • Intermediate use of NetLogo

Course leader

Reading list

  • Gilbert, N. (2008), Agent-Based Models, Quantitative Applications in the Social Sciences, Sage Publications, pp.153.
  • Gilbert, N. and Troitzsch, K. (2005) Simulation for the Social Scientist, Oxford University Press.
  • Squazzoni, F, Jager, W. and Edmonds B. (2014) Social Simulation: A Brief Overview, Social Science Computer Review, 32(3).

Class size

Maximum of 20 people. Please note, 10 participants will be students from our MSc Social Research Methods course.

Entry requirements

There are no formal entry requirements for this course.

Fees and funding

Price per person:


Government and commercial sector applicants


Education and charitable sector applicants



How to apply

Applications for this course are currently closed.

Register your interest

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This online prospectus has been prepared and published in advance of the commencement of the course. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read more.