Computational Model Library

This model is an agent-based simulation written in Python 2.7, which simulates the cost of social care in an ageing UK population. The simulation incorporates processes of population change which affect the demand for and supply of social care, including health status, partnership formation, fertility and mortality. Fertility and mortality rates are drawn from UK population data, then projected forward to 2050 using the methods developed by Lee and Carter 1992.

The model demonstrates that rising life expectancy combined with lower birthrates leads to growing social care costs across the population. More surprisingly, the model shows that the oft-proposed intervention of raising the retirement age has limited utility; some reductions in costs are attained initially, but these reductions taper off beyond age 70. Subsequent work has enhanced and extended this model by adding more detail to agent behaviours and familial relationships.

The version of the model provided here produces outputs in a format compatible with the GEM-SA uncertainty quantification software by Kennedy and O’Hagan. This allows sensitivity analyses to be performed using Gaussian Process Emulation.

The purpose of this model is to understand the role of trade networks and their interaction with different fish resources, for fish provision. The model is developed based on a multi-methods approach, combining agent-based modeling, network analysis and qualitative data based on a small-scale fisheries study case. The model can be used to investigate both how trade network structures are embedded in a social-ecological context and the trade processes that occur within them, to analyze how they lead to emergent outcomes related to the resilience of fish provision. The model processes are informed by qualitative data analysis, and the social network analysis of an empirical fish trade network. The network analysis can be used to investigate diverse network structures to perform model experiments, and their influence on model outcomes.

The main outcomes we study are 1) the overexploitation of fish resources and 2) the availability and variability of fish provision to satisfy different market demands, and 3) individual traders’ fish supply at the micro-level. The model has two types of trader agents, seller and dealer. The model reveals that the characteristics of the trade networks, linked to different trader types (that have different roles in those networks), can affect the resilience of fish provision.

AgentEx aims to advance understanding of group processes for sustainable management of a common pool resource (CPR). By supporting the development and test explanations of cooperation and sustainable exploitation.

Team Cognition

Iris Lorscheid | Published Sun May 23 14:25:17 2021

The teamCognition model investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model’s construction, as well as data for an output validation of the model. The agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions.

MCR Model

Davide Secchi Nuno R Barros De Oliveira | Published Fri Jul 22 08:59:51 2016 | Last modified Sat Jan 23 20:20:27 2021

The aim of the model is to define when researcher’s assumptions of dependence or independence of cases in multiple case study research affect the results — hence, the understanding of these cases.

The model simulates agents in a spatial environment competing for a common resource that grows on patches. The resource is converted to energy, which is needed for performing actions and for surviving.

Peer reviewed MOOvPOPsurveillance

Aniruddha Belsare Matthew Gompper Joshua J Millspaugh | Published Tue Apr 4 17:03:40 2017 | Last modified Tue May 12 16:37:24 2020

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Peer reviewed MOOvPOP

Aniruddha Belsare Matthew Gompper Joshua J Millspaugh | Published Mon Apr 10 20:03:42 2017 | Last modified Tue May 12 06:14:14 2020

MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.


Gudrun Wallentin | Published Tue Apr 21 07:20:07 2020 | Last modified Tue Apr 21 08:59:02 2020

Model of the Corona pandemic outbreak

The COVID-19 ABM aims to predict the qualitative behaviour of the CoViD-19 epidemic dynamics for the greater region of Salzburg City. Specifically, by means of scenario testing, it aims to help assessing how containment interventions can allow a stepwise relaxation of the lockdown without risking a new outbreak.

Peer reviewed Neighbor Influenced Energy Retrofit (NIER) agent-based model

Eric Boria | Published Fri Apr 3 02:19:28 2020

The NIER model is intended to add qualitative variables of building owner types and peer group scales to existing energy efficiency retrofit adoption models. The model was developed through a combined methodology with qualitative research, which included interviews with key stakeholders in Cleveland, Ohio and Detroit and Grand Rapids, Michigan. The concepts that the NIER model adds to traditional economic feasibility studies of energy retrofit decision-making are differences in building owner types (reflecting strategies for managing buildings) and peer group scale (neighborhoods of various sizes and large-scale Districts). Insights from the NIER model include: large peer group comparisons can quickly raise the average energy efficiency values of Leader and Conformist building owner types, but leave Stigma-avoider owner types as unmotivated to retrofit; policy interventions such as upgrading buildings to energy-related codes at the point of sale can motivate retrofits among the lowest efficient buildings, which are predominantly represented by the Stigma-avoider type of owner; small neighborhood peer groups can successfully amplify normal retrofit incentives.

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