Computational Model Library

The model combines agent-based modelling and microeconomic approach to simulate the decision behaviour of land developers and how this impacts on the spatio-temporal processes of urban expansion.

Transport simulation in a real road network

Jiaqi Ge Gary Polhill | Published Tue Apr 17 15:01:37 2018 | Last modified Tue Apr 17 15:06:43 2018

Ge, J., & Polhill, G. (2016). Exploring the Combined Impact of Factors Influencing Commuting Patterns and CO2 Emission in Aberdeen Using an Agent-Based Model. Journal of Artificial Societies and Social Simulation, 19(3).
We develop an agent-based transport model using a realistic GIS-enabled road network and the car following method. The model can be used to study the impact of social interventions such as flexi-time and workplace sharing, as well as large infrastructure such as the construction of a bypass or highway. The model is developed in Netlogo version 5 and requires road network data in GIS format to run.

Simulation of the Governance of Complex Systems

Fabian Adelt Johannes Weyer Robin D Fink Andreas Ihrig | Published Mon Dec 18 16:11:30 2017 | Last modified Fri Mar 2 09:37:16 2018

Simulation-Framework to study the governance of complex, network-like sociotechnical systems by means of ABM. Agents’ behaviour is based on a sociological model of action. A set of basic governance mechanisms helps to conduct first experiments.

Last Mile Commuter Behavior Model

Moira Zellner Dean Massey Yoram Shiftan Jonathan Levine Maria Arquero | Published Fri Nov 7 19:47:59 2014 | Last modified Fri Nov 7 19:53:35 2014

We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.

A proof-of-concept agent-based model ‘SimDrink’, which simulates a population of 18-25 year old heavy alcohol drinkers on a night out in Melbourne to provide a means for conducting policy experiments to inform policy decisions.

Mobility USA (MUSA)

Davide Natalini Giangiacomo Bravo | Published Sun Dec 8 19:24:09 2013 | Last modified Mon Dec 30 19:22:17 2013

MUSA is an ABM that simulates the commuting sector in USA. A multilevel validation was implemented. Social network with a social-circle structure included. Two types of policies have been tested: market-based and preference-change.

Feedback Loop Example: Forest Resource Transport

James Millington | Published Fri Dec 21 11:11:07 2012 | Last modified Sat Apr 27 20:18:32 2013

This model illustrates a positive ‘transport’ feedback loop in which lines with different resistance to flows of material result in variation in rates of change in linked entities.

Modeling the Emergence of Riots

Bianica Pires Andrew Crooks | Published Wed Jan 20 14:06:58 2016 | Last modified Wed Sep 21 13:28:10 2016

The purpose of the model is to explore how the unique socioeconomic variables underlying Kibera, local interactions, and the spread of a rumor, may trigger a riot.

We present an agent-based model that maps out and simulates the processes by which individuals within ecological restoration organizations communicate and collectively make restoration decisions.


Elena Maggi Elena Vallino | Published Tue Jan 31 16:04:05 2017 | Last modified Fri Aug 4 15:48:28 2017

This ABM deals with commuting choices in the Italian city of Varese. Empirical data inform agents’ attitudes and modal choices costs and emissions. We evaluate ex ante the impact of policies for less polluting commuting choices.

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