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Social Simulation Tutorial. International Symposium on Grid Computing Taipei, Taiwan, 7 th March 2010. Agenda. The Team. Alex Voss School of Computer Science University of St Andrews Andy Turner School of Geography University of Leeds

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social simulation tutorial

Social Simulation Tutorial

International Symposium on Grid ComputingTaipei, Taiwan, 7th March 2010

the team
The Team
  • Alex VossSchool of Computer ScienceUniversity of St Andrews
  • Andy TurnerSchool of GeographyUniversity of Leeds
  • Rob ProcterManchester e-Research CentreUniversity of Manchester
aims of the tutorial
Aims of the Tutorial
  • To provide a brief introduction to agent-based simulation, population reconstruction and RePast Simphony.
  • To motivate the use of grids and clouds for running social simulation ensembles
  • To demonstrate use of grids and clouds and provide practical instructions for running your own models
  • Not to replace RePast tutorial!
  • Using your own laptop
  • Participant sheet with login
  • URL for instructions:
  • Download software and certificates from local server (see URL above) – also USB sticks to pass around
  • Using GILDA training infrastructure
  • Much social science does not use advanced ICT but emergence of new analytical methods is driven by:
    • Increased availability of data about social phenomena
    • But data is ‘messy’, anonymised, aggregated, incomplete
    • Challenges to analyse social phenomena at scale
    • Challenges to inform practical policy and decision making (e.g., evidence-based policy making)
what is social simulation
What is Social Simulation?
  • A new approach to modeling social phenomena
  • Based on empirical data
  • Based on existing theories
  • A new way to explore them, complementing other forms of modelling and prediction
  • Used to understand and predict
  • Not just one form of simulation: systems dynamics, microsimulation, queueing models, etc.
what is social simulation ii
What is Social Simulation? (II)
  • Models necessarily incomplete
  • There can always be more detail
    • Higher spatial and temporal resolution
    • More and more detailed attributes
    • Geography and social science is no different to any other type of science in this respect
  • Need to assess impact of decision about how to model
simulation as a method
Simulation as a Method


Simulated Data


Implementation and Verification





Collected Data

Data Gathering

or Re-Use


Adapted from Gilbert & Troitzsch, p. 17

what is agent based modelling
What is Agent-Based Modelling?
  • Simulating interactions between dynamic populations in changing environment
  • Heterogeneous populations – each individual has specific attributes such as age, gender, socio-economic status, health, etc.
  • Stochastic process – each run can differ from previous
  • Notion of emergence – larger-scale phenomena produced through many small interactions / events
  • Sets of simple rules produce complex behaviour – sets can be large…
  • Can help model and analyse phenomena too complex for closed form, can be used in absence of knowledge about causality
abm frameworks
ABM Frameworks
  • Rapid growth over last 10 years
  • Many implementations
  • General frameworks (open source):
    • Swarm
    • MASON
    • NetLogo
    • Repast
    • Repast Simphony
  • Aim to separate concerns clearly to maximise modeling capability
abm conceptual components
ABM Conceptual Components






building simulation models
Building Simulation Models
  • Model Design – about the choices made, cf. research design
  • Model implementation – cf. research method (‘the logistics’, ‘plumbing’)
  • Verification – checking the implementation matches the design
  • Validation – checking the design represents the aspects of the world modeled
building simulation models ii
Building Simulation Models (II)
  • Simple models can be built using graphical editors (cf. RePast tutorial)
  • More complex models and behaviours inevitably require programming
  • Data management etc. become important as size grows
  • Calls for interdisciplinary collaboration, division of labour see above
trust in models
Trust in Models
  • Scientific codes often many years old and carefully maintained
  • Social simulation is in its infancy – relatively speaking
  • Need to build community development approaches that produce robust, reliable code
  • Yet need for flexibility and adaptability – research is about doing things not done before…
social simulation reading
Social Simulation: Reading
  • Nigel Gilbert and Klaus G. Troitzsch: Simulation for the Social Scientist(
  • Joshua M. EpsteinGenerative Social Science:Studies in Agent-Based Computational Modeling(