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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A simulated approach for Personal Carbon Trading, for figuring out what effects it might have if it will be implemented in the real world. We use an artificial population with some empirical data from international literature and basic assumptions about heterogeneous energy demand. The model is not to be used as simulating the actual behavior of real populations, but a toy model to test the effects of differences in various factors such as number of agents, energy price, price of allowances, etc. It is important to adapt the model for specific countries as carbon footprint and energy demand determines the relative success of PCT.
The Retail Competition Agent-based Model (RC-ABM) is designed to simulate the retail competition system in the Region of Waterloo, Ontario, Canada, which which explicitly represents store competition behaviour. Through the RC-ABM, we aim to answer 4 research questions: 1) What is the level of correspondence between market share and revenue acquisition for an agent-based approach compared to a traditional location-allocation-based approach? 2) To what degree can the observed store spatial pattern be reproduced by competition? 3) To what degree are their path dependent patterns of retail success? 4) What is the relationship between retail survival and the endogenous geographic characteristics of stores and consumer expenditures?
The model is suitable to investigate the effects of different characteristics of apprenticeship programmes both in historical and contemporary societies. The model is built considering five societies, using an agent-based simulation model, we identified six main characteristics which impact the success of an apprenticeship programme in a society, which we measured by considering three parameters, namely the number of skilled agents produced by the apprenticeships, programme completion, and the contribution of programmes in the Gross Domestic Income (GDI) of the society. We investigate different definitions for success of an apprenticeship and some hypothetical societies to test some common beliefs about apprenticeships performance. The model also shows the number of unemployed agents given their work-based skills, wages, and the number of small and large companies who participate in training agents. The model enables exploring the impact of parameters, such as initial wages and the number of training years, along with the stated policies on the system.
Our aim is to show effects of group living when only low-level cognition is assumed, such as pattern recognition needed for normal functioning, without assuming individuals have knowledge about others around them or warn them actively.
The model is of a group of vigilant foragers staying within a patch, under attack by a predator. The foragers use attentional scanning for predator detection, and flee after detection. This fleeing action constitutes a visual cue to danger, and can be received non-attentionally by others if it occurs within their limited visual field. The focus of this model is on the effectiveness of this non-attentional visual information reception.
A blind angle obstructing cue reception caused by behaviour can exist in front, morphology causes a blind angle in the back. These limitations are represented by two visual field shapes. The scan for predators is all-around, with distance-dependent detection; reception of flight cues is limited by visual field shape.
Initial parameters for instance: group sizes, movement, vision characteristics for predator detection and for cue reception. Captures (failure), number of times the information reached all individuals at the same time (All-fled, success), and several other effects of the visual settings are recorded.
Extension of Pluchino et al.’s 2018 success vs talent model, to allow talented individuals to mitigate unlucky events.
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
Trust between farmers and processors is a key factor in developing stable supply chains including “bottom of the pyramid”, small-scale farmers. This simulation studies a case with 10000 farmers.
We built an agent-based model to foster the understanding of homeowners’ insulation activity.
The purpose of this model is to provide a platform to test and compare four conceptual models have been proposed to explain the spread of the Impresso-Cardial Neolithic in the west Mediterranean.
This is a model of a community of online communities. Using mechanisms such as win-stay, lose-shift, and preferential attachment the model can reproduce similar patterns to those of the Stack Exchange network.
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