Computational Model Library

SWIM is a simulation of water management, designed to study interactions among water managers and customers in Phoenix and Tucson, Arizona. The simulation can be used to study manager interaction in Phoenix, manager and customer messaging and water conservation in Tucson, and when coupled to the Water Balance Model (U New Hampshire), impacts of management and consumer choices on regional hydrology.


Murphy, John T., Jonathan Ozik, Nicholson T. Collier, Mark Altaweel, Richard B. Lammers, Alexander A. Prusevich, Andrew Kliskey, and Lilian Alessa. “Simulating Regional Hydrology and Water Management: An Integrated Agent-Based Approach.” Winter Simulation Conference, Huntington Beach, CA, 2015.

The model aims at estimating household energy consumption and the related greenhouse gas (GHG) emissions reduction based on the behavior of the individual household under different operationalizations of the Theory of Planned Behaviour (TPB).
The original model is developed as a tool to explore households decisions regarding solar panel investments and cumulative consequences of these individual choices (i.e. diffusion of PVs, regional emissions savings, monetary savings). We extend the model to explore a methodological question regarding an interpretation of qualitative concepts from social science theories, specifically Theory of Planned Behaviour in a formal code of quantitative agent-based models (ABMs). We develop 3 versions of the model: one TPB-based ABM designed by the authors and two alternatives inspired by the TPB-ABM of Schwarz and Ernst (2009) and the TPB-ABM of Rai and Robinson (2015). The model is implemented in NetLogo.

Previous work with the spatial iterated prisoner’s dilemma has shown that “walk away” cooperators are able to outcompete defectors as well as cooperators that do not respond to defection, but it remains to be seen just how robust the so-called walk away strategy is to ecologically important variables such as population density, error, and offspring dispersal. Our simulation experiments identify socio-ecological conditions in which natural selection favors strategies that emphasize forgiveness over flight in the spatial iterated prisoner’s dilemma. Our interesting results are best explained by considering how population density, error, and offspring dispersal affect the opportunity cost associated with walking away from an error-prone partner.

An Agent-Based Simulation of Continuous-Time Public Goods Games

Tuong Vu | Published Thu May 17 10:39:29 2018 | Last modified Tue Apr 2 09:28:13 2019

To our knowledge, this is the first agent-based simulation of continuous-time PGGs (where participants can change contributions at any time) which are much harder to realise within both laboratory and simulation environments.

Work related to this simulation has been published in the following journal article:
Vu, Tuong Manh, Wagner, Christian and Siebers, Peer-Olaf (2019) ‘ABOOMS: Overcoming the Hurdles of Continuous-Time Public Goods Games with a Simulation-Based Approach’ Journal of Artificial Societies and Social Simulation 22 (2) 7 doi: 10.18564/jasss.3995


RHEA aims to provide a methodological platform to simulate the aggregated impact of households’ residential location choice and dynamic risk perceptions in response to flooding on urban land markets. It integrates adaptive behaviour into the spatial landscape using behavioural theories and empirical data sources. The platform can be used to assess: how changes in households’ preferences or risk perceptions capitalize in property values, how price dynamics in the housing market affect spatial demographics in hazard-prone urban areas, how structural non-marginal shifts in land markets emerge from the bottom up, and how economic land use systems react to climate change. RHEA allows direct modelling of interactions of many heterogeneous agents in a land market over a heterogeneous spatial landscape. As other ABMs of markets it helps to understand how aggregated patterns and economic indices result from many individual interactions of economic agents.
The model could be used by scientists to explore the impact of climate change and increased flood risk on urban resilience, and the effect of various behavioural assumptions on the choices that people make in response to flood risk. It can be used by policy-makers to explore the aggregated impact of climate adaptation policies aimed at minimizing flood damages and the social costs of flood risk.

Agent-based model for centralized student admission process

Connie Wang Bin-Tzong Chi Shu-Heng Chen | Published Wed Nov 4 20:41:02 2015 | Last modified Wed Mar 6 00:49:36 2019

This model is to match students and schools using real-world student admission mechanisms. The mechanisms in this model are serial dictatorship, deferred acceptance, the Boston mechanism, Chinese Parallel, and the Taipei mechanism.

An Agent-Based School Choice Matching Model

Connie Wang Weikai Chen Shu-Heng Chen | Published Sun Feb 1 13:19:48 2015 | Last modified Wed Mar 6 00:49:06 2019

This model is to simulate and compare the admission effects of 3 school matching mechanisms, serial dictatorship, Boston mechanism, and Chinese Parallel, under different settings of information released.

Institutional change

Abigail Sullivan | Published Fri Oct 7 20:35:15 2016 | Last modified Sun Dec 2 04:27:11 2018

This model builds on another model in this library (“diffusion of culture”).

The purpose of the OMOLAND-CA is to investigate the adaptive capacity of rural households in the South Omo zone of Ethiopia with respect to variation in climate, socioeconomic factors, and land-use at the local level.

The Regional Security Game is a iterated public goods game with punishement based on based on life sciences work by Boyd et al. (2003 ) and Hintze & Adami (2015 ), with modifications appropriate for an international relations setting. The game models a closed regional system in which states compete over the distribution of common security benefits. Drawing on recent work applying cultural evolutionary paradigms in the social sciences, states learn through imitation of successful strategies rather than making instrumentally rational choices. The model includes the option to fit empirical data to the model, with two case studies included: Europe in 1933 on the verge of war and south-east Asia in 2013.

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