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School of GeographyFACULTY OF ENVIRONMENT

The Elements of a Computational Infrastructure for Social Simulation

Mark Birkin1, Rob Allan2, Sean Beckhofer3, Iain Buchan4, June Finch5, Carole Goble3, Andy Hudson-Smith6, Paul

Lambert7, Rob Procter5, David de Roure8, Richard Sinnott9

[1] School of Geography, University of Leeds [2] STFC, Daresbury [3] School of Computer Science, University of Manchester [4] School of Medicine, University of Manchester

[5] School of Social Sciences, University of Manchester [6] Centre for Applied Spatial Analysis, UCL[7] Applied Social Science, University of Stirling [8] Electronics and Computer Science, University of

Southampton [9] NeSC, University of Glasgow

6649386

Simulation of Epidemics

Ferguson et al, Nature, 2006

The El Farol Bar Problem

Everyone wants to go the bar

- unless it’s too crowded!

Must relax neoclassical economic assumptions (homogeneity of preferences, simultaneous decision-making)

Individual actors/ agent-based decision-making

- generic template for real markets

heterogeneous

out of equilibrium

(Arthur, 1994)

Public Policy

Source: MAPS2030

2001 2031

2015

* Traffic Intensity=Traffic load/Road capacity

0

0.1

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0.3

0.4

0.5

0.6

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0.8

0.9

1.0

Traffic Intensity *

Transport…

Social Simulation

Applications

Economics, geography, sociology

Health sciences, politics, anthropology

Methods

Agent-based models

Microsimulation

Impact

Theory to policy

Analysis, projection, forecasting, scenarios

Features of social simulation

Widespread data requirements

Plug-and-play simulation and analysis components

Visualise complex outcomes

Computationally demanding

Need to reproduce and share results with a community of users

Rationale for NeISS

Growing demand for social simulation models

Critical mass in NCeSS

International collaboration with solid foundations

Ongoing innovation

Leverage existing investments in computation and data

NeISS Architecture

NeISS Architecture

NeISS Portal

NeISS Portal

School of GeographyFACULTY OF ENVIRONMENT

Conclusion

NeISS will:

Combine research lifecycle elements within a unified social simulation infrastructure

Leverage skills and relationships from the UK e-social science programme (NCeSS)

Build user communities in both public policy and academia

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