Agent-Based Modelling for the Social Scientist
Attendance dates:To be confirmed
Time commitment: 3 days
Stag Hill campus, University of Surrey, Guildford, Surrey GU2 7XH
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.
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)
- 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
Corinna ElsenbroichSee profile
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).
Maximum of 20 people. Please note, 10 participants will be students from our MSc Social Research Methods course.
There are no formal entry requirements for this course.
Fees and funding
Price per person:
£595Government and commercial sector applicants
£495Education and charitable sector applicants
Terms and conditions
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