Centre for Policy Modelling News

News from the Centre for Policy Modelling, including announcements of: new papers, special issues, books, workshops, projects, jobs and study opportunities.

03 June, 2015

Special Demonstration Session on Policy and Agent-Based Simulation @ ACM SIGSIM PADS, London 11th June

As part of ESSA's attempts to bridge gaps with other fields there will be a special demonstration session at the ACM Simulation SIG on Principles of Advanced Discrete Simulation meeting, that is happening at the University of Westminster, London, June 10-12, 2015.

This special session will showcase ABM policy simulation work, and will happen on the 11th June 2-3.30pm.

The papers will be:



Bridging Relevance with Rigour in the Policy Modelling of Political Participation
Bruce Edmonds (Centre for Policy Modelling, Manchester Metropolitan University, UK), Luis Fernandez Lafuerza (Department of Theoretical Physics, University of Manchester, UK), Louise Dyson (Department of Theoretical Physics, University of Manchester, UK), Laurence Lessard-Phillips (Institute for Social Change, University of Manchester, UK), Ed Fieldhouse (Institute for Social Change, University of Manchester, UK), and Alan McKane (Department of Theoretical Physics, University of Manchester, UK)
Agent-Based Modelling for Exploring Policies in Complex Socio-Environmental Systems
Gary Polhill, Jiaqi Ge, Alessandro Gimona, and Nick Gotts (James Hutton Institute, UK)
Multi-Agent Simulation and Animation with PreSage-2
Jeremy Pitt (Imperial College, UK)

07 February, 2015

Social Simulation 2015 @ Gronigen in the Netherlands

The Eleventh Conference of the European Social Simulation Association

Join us from September 14 to 18 in Groningen (NL)

Deadline for submissions: April 13th 2015

More details: http://essa2015.org

02 February, 2015

Special Section of JASSS published on "Using Qualitative Evidence to Inform the Specification of Agent-Based Models"

See http://jasss.soc.surrey.ac.uk/ (http://jasss.soc.surrey.ac.uk/18/1 for a more permenant but less nicely formatted link).

The introduction to the issue is:
Edmonds, Bruce (2015) 'Using Qualitative Evidence to Inform the Specification of Agent-Based Models' Journal of Artificial Societies and Social Simulation 18(1):18 <http://jasss.soc.surrey.ac.uk/18/1/18.html>.
 This is the culmination of the workshops and special sessions of "Social Simulation" (ESSA) conferences on the subject.  Many thanks to all who contributed!

08 November, 2014

Registration for Workshop on Modelling Routines open for 12 days

Registration for the workshop on "Modelling Routines" is now open, until the 20th November.  Registration is free but essential if you are going to attend.

Register here:
http://www.eventbrite.com/e/modelling-routines-workshop-tickets-14190346709

The draft programme for the day includes an invited talk by Alan Warde, Professor of Sociology, at the University of Manchester’s “Sustainable Consumption Institute”, http://www.sci.manchester.ac.uk/people/professor-alan-warde

Plus contributed papers as follows:
  • Daniel F├╝rstenau. Exploring Interrelated Routine Dynamics from a Network Perspective: A Campus Management Case and Conceptual Model
  • Philipp Singer, Denis Helic, Andreas Hotho and Markus Strohmaier. Bayesian Comparison of Hypotheses about Human Trails on the Web
  • James Doran. An AI Oriented Question: are there Routines that Adjust Routines to Achieve Effective Cooperation?
  • Cara H. Kahl and Matthias Meyer. Contemporary agent-based models of organizational routines
  • Edmund Chattoe-Brown. Three Case Studies in the Evolution of Routines: False Starts and New Opportunities
  • Dermot Breslin. Conceptualizing and Modeling Multi-Level Organizational Co-Evolution
  • Bruce Edmonds, Projection and the Reality of RoutinesTina Balke and Thomas Roberts. Modelling Practices and Routines – Where are the households?

The workshop website is at: http://modellingroutines.wordpress.com/

13 October, 2014

New Model available: A Complex Model of Voter Turnout

Please cite as:
Edmonds, Bruce, Lessard-Phillips, Laurence, Fieldhouse, Ed (2014, October 13). "A Complex Model of Voter Turnout" (Version 1). CoMSES Computational Model Library. Retrieved from: https://www.openabm.org/model/4368
Developed as part of the SCID project.

Abstract
This is intended as a “Data Integration Model” (Edmonds 2010b). That is a consistent, detailed and dynamic description, in the form of an agent-based simulation, of the available evidence concerning the question of why people bother to vote. This integrates a variety of kinds and qualities of evidence. Thus it follows a “KIDS” rather than a “KISS” methodology - it aims to be more guided by the available evidence rather than simplicity (Edmonds & Moss 2005).

Thus this is a complex model, with many different social processes interweaving. Although not specifically designed as such, it turns out that the model has distinct “layers”. These are:
  • The input data which initialises the agents in new households (at the start or in-coming households)
  • The demographic processes: immigration, emmigration, partnering, birth, death, ageing etc.
  • The social network that develops and changes between agents (representing a relationship that would allow a political discussion if the agents were so minded)
  • The social influence via political discussions that can occur over the network
  • The decisions and processes which determine whether agents vote or not
The purpose of this model is to enable the exploration of some social processes behind voter turnout, including demographic trends in household size and composition, social influence via the social networks the individuals are embedded within, wider social norms such as civic duty, personal habit and identity, as well as individual rationality. Thus this model is an explanatory model - it demonstrates the plausibility of (complicated) explanations of outcomes from the initial set-up.

It is important to understand that this is NOT a simulation with free-parameters that are conditioned on some “in-sample” data. It does have a lot of parameters, but these are set (or could be set) from empirical data.