Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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We also maintain a curated database of over 7500 publications of agent-based and individual based models with 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 presented ABM is to explore how system resilience is affected by external disturbances and internal dynamics by using the stylized model of an agricultural land use system.
We explore land system resilience with a stylized land use model in which agents’ land use activities are affected by external shocks, agent interactions, and endogenous feedbacks. External shocks are designed as yield loss in crops, which is ubiquitous in almost every land use system where perturbations can occur due to e.g. extreme weather conditions or diseases. Agent interactions are designed as the transfer of buffer capacity from farmers who can and are willing to provide help to other farmers within their social network. For endogenous feedbacks, we consider land use as an economic activity which is regulated by markets — an increase in crop production results in lower price (a negative feedback) and an agglomeration of a land use results in lower production costs for the land use type (a positive feedback).
This model simulate product diffusion on different social network structures.
A dynamic model of social network formation on single-layer and multiplex networks with structural incentives that vary over time.
The model employs an agent-based model for exploring the victim-centered approach to identifying human trafficking and the approach’s effectiveness in an abstract representation of migrant flows.
The model presented here was created as part of my dissertation. It aims to study the impacts of topography and climate change on prehistoric networks, with a focus on the Magdalenian, which is dated to between 20 and 14,000 years ago.
This generic model simulates climate change adaptation in the form of resistance, accommodation, and retreat in coastal regions vulnerable to sea level rise and flooding. It tracks how population changes as households retreat to higher ground.
This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.
The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.
We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.
An agent-based framework that aggregates social network-level individual interactions to run targeting and rewarding programs for a freemium social app. Git source code in https://bitbucket.org/mchserrano/socialdynamicsfreemiumapps
Displaying 10 of 75 results social network clear search