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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Resilience of humans in the Upper Paleolithic could provide insights in how to defend against today’s environmental threats. Approximately 13,000 years ago, the Laacher See volcano located in present-day western Germany erupted cataclysmically. Archaeological evidence suggests that this is eruption – potentially against the background of a prolonged cold spell – led to considerable culture change, especially at some distance from the eruption (Riede, 2017). Spatially differentiated and ecologically mediated effects on contemporary social networks as well as social transmission effects mediated by demographic changes in the eruption’s wake have been proposed as factors that together may have led to, in particular, the loss of complex technologies such as the bow-and-arrow (Riede, 2014; Riede, 2009).
This model looks at the impact of the interaction between climate change trajectory and an extreme event, such as the Laacher See eruption, on the generational development of hunter-gatherer bands. Historic data is used to model the distribution and population dynamics of hunter-gatherer bands during these circumstances.
The purpose of the model presented by Glance et al is to study the ‘contribute vs. free-ride’ dilemma present in organizations.
The model simulates the process of widespread diffusion of something due to popularity (i.e., bandwagon) within an organization.
This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.
BorealFireSIM is a cellular automaton based model that serves to identify future fire patterns in the boreal forest of Quebec, Canada. The model simulates yearly fire seasons and adjusts decadal climate variables based on two future carbon pathways (RCP45 (low emissions) and RCP85 (business as usual)). The BorealFireSIM model simulates future fire patterns up to the year 2100.
This model simulates the Hawk-Dove game as first described by John Maynard Smith, and further elaborated by Richard Dawkins in “The Selfish Gene”. In the game, two strategies, Hawks and Doves, compete against each other, and themselves, for reproductive benefits. A third strategy can be introduced, Retaliators, which act like either Hawks or Doves, depending on the context.
This is an urban dynamics ABM of abstraction of a city and residents’ activities there.
It allows you to evaluate the effects of urban policies, such as an introduction of an open facility for residents with pedestrian-friendly accommodations, promotion of bicycle use, and control of private automobile use in an urban central area, in controlling urban sprawl.
This is an agent-based model constructed in Netlogo v6.2.2 which seeks to provide a simple but flexible tool for researchers and dog-population managers to help inform management decisions.
It replicates the basic demographic processes including:
* reproduction
* natural death
* dispersal
…
Micro-targeted vs stochastic political campaigning agent-based model simulation. Written by Toby D. Pilditch (University of Oxford, University College London), in collaboration with Jens K. Madsen (University of Oxford, London School of Economics)
The purpose of the model is to explore the various impacts on voting intention among a population sample, when both stochastic (traditional) and Micto-targeted campaigns (MTCs) are in play. There are several stages of the model: initialization (setup), campaigning (active running protocols) and vote-casting (end of simulation). The campaigning stage consists of update cycles in which “voters” are targeted and “persuaded” - updating their beliefs in the campaign candidate / policies.
Interactions of players embedded in a closed square lattice are determined by distance and overall gains and they lead to shifts of reward payoff between temptation and punishment. A new winner balancing against threats is ultimately discovered.
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