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.
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 feel free to contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
Displaying 10 of 1012 results for "Chantal van Esch" clear search
An agent-based model simulating West Nile Virus dynamics in a one host (American robin)-one vector (Culex spp. mosquito) system. ODD improved and code cleaned.
Ants in the genus Temnothorax use tandem runs (rather than pheromone trails) to recruit to food sources. This model explores the collective consequences of this linear recruitment (as opposed to highly nonlinear pheromone trails).
This model simulates the mechanisms of evolution, or how allele frequencies change in a population over time.
The model represents an archetypical fishery in a co-evolutionary social-ecological environment, capturing different dimensions of trust between fishers and fish buyers for the establishment and persistence of self-governance arrangements.
NeoCOOP is an iteration-based ABM that uses Reinforcement Learning and Artificial Evolution as adaptive-mechanisms to simulate the emergence of resource trading beliefs among Neolithic-inspired households.
This is based off my previous Profiler tutorial model, but with an added tutorial on converting it into a model usable with BehaviorSpace, and creating a BehaviorSpace experiment.
WatASit is an agent-based model implemented in the CORMAS plateform. The model is developped to simulate irrigation situations at the operational level during a collective irrigation campaign.
An agent-based microsimulation of insecticide-treated net (ITN) distribution and adoption in Kenya (2003–2024), integrating the Theory of Planned Behaviour, Rogers diffusion, Weibull net decay, and a GPS-based two-layer social network. 8,561 household agents calibrated via Approximate Bayesian Computation to six DHS/MIS survey waves, achieving 2.42 pp mean absolute error on Kenya-level ownership. The analysis chain supports mechanism counterfactuals and policy experiments on equity outcomes of ITN distribution strategies.
An agent model is presented that aims to capture the impact of cheap talk on collective action in a commons dilemma. The commons dilemma is represented as a spatially explicit renewable resource. Agent’s trust in others impacts the speed and harvesting rate, and trust is impacted by observed harvesting behavior and cheap talk. We calibrated the model using experimental data (DeCaro et al. 2021). The best fit to the data consists of a population with a small frequency of altruistic and selfish agents, and mostly conditional cooperative agents sensitive to inequality and cheap talk. This calibrated model provides an empirical test of the behavioral theory of collective action of Elinor Ostrom and Humanistic Rational Choice Theory.
This model is an abstract simulation of the COVID-19 virus in the United States population. It demonstrates how different masks of different types affect the progress of the virus.
Displaying 10 of 1012 results for "Chantal van Esch" clear search