Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
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The purpose of the model is to explore the influence of the design of circular business models (CBMs) on CBM viability. The model represents an Industrial Symbiosis Network (ISN) in which a processor uses the organic waste from suppliers to produce biogas and nutrient rich digestate for local reuse. CBM viability is expressed as value captured (e.g., cash flow/tonne waste/agent) and the survival of the network over time (shown in the interface).
In the model, the value captured is calculated relative to the initial state, using incineration costs as a benchmark. Moderating variables are interactions with the waste incinerator and actor behaviour factors. Actors may leave the network when the waste supply for local production is too low, or when personal economic benefits are too low. When the processor decides to leave, the network fails. Theory of planned behaviour can be used to include agent behaviour in the simulations.
This is a generic sub-model of animal territory formation. It is meant to be a reusable building block, but not in the plug-and-play sense, as amendments are likely to be needed depending on the species and region. The sub-model comprises a grid of cells, reprenting the landscape. Each cell has a “quality” value, which quantifies the amount of resources provided for a territory owner, for example a tiger. “Quality” could be prey density, shelter, or just space. Animals are located randomly in the landscape and add grid cells to their intial cell until the sum of the quality of all their cells meets their needs. If a potential new cell to be added is owned by another animal, competition takes place. The quality values are static, and the model does not include demography, i.e. mortality, mating, reproduction. Also, movement within a territory is not represented.
This ABM aims to introduce a new individual decision-making model, BNE into the ABM of pedestrian evacuation to properly model individual behaviours and motions in emergency situations. Three types of behavioural models has been developed, which are Shortest Route (SR) model, Random Follow (RF) model, and BNE model, to better reproduce evacuation dynamics in a tunnel space. A series of simulation experiments were conducted to evaluate the simulating performance of the proposed ABM.
This generic individual-based model of a bird colony shows how the influence neighbour’s stress levels synchronize the laying date of neighbours and also of large colonies. The model has been used to demonstrate how this form of simulation model can be recognised as being ‘event-driven’, retaining a history in the patterns produced via simulated events and interactions.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. Plus, the code for graphical output is also added to the original code.
This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts.
This is an adaptation and extension of Robert Axtell’s model (2013) of endogenous firms, in Python 3.4
This is an agent-based model designed to explore the evolution of cooperation under changes in resources availability for a given population
Organisms, Individuals and Organizations face the dilemma of exploration vs. exploitation
Identifying the optimal trade-off between the two is a challenge
Too much exploration (e.g. gaining new knowledge) can be detrimental to day-to-day survival and too much exploitation (applying existing knowledge) could be detrimental to long term survival esp. if conditions change over time
The purpose of the model is to investigate how the amount of resources acquired (wealth/success) is related to persistence with the strategy of local exploration under different resource distributions, availability of resources over time and cost of relocation
This model takes into consideration Peer Reviewing under the influence of Impact Factor (PRIF) and it has the purpose to explore whether the infamous metric affects assessment of papers under review. The idea is to consider to types of reviewers, those who are agnostic towards IF (IU1) and those that believe that it is a measure of journal (and article) quality (IU2). This perception is somehow reflected in the evaluation, because the perceived scientific value of a paper becomes a function of the journal in which an article has been submitted. Various mechanisms to update reviewer preferences are also implemented.
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