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 Inspection Model represents a basic food safety system where inspectors, consumers and stores interact. The purpose of the model is to provide insight into an optimal level of inspectors in a food system by comparing three search strategies.
The Inspection Model represents a basic food safety system where inspectors, consumers and stores interact. The purpose of the model is to provide insight into an optimal level of inspectors in a food system by comparing three search strategies.
We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.
The model reproduces the spread of environmental awareness among agents and the impact of awareness level of the agents on the consumption of a resource, like energy. An agent is a household with a set of available advanced smart metering functions.
What is stable: the large but coordinated change during a diffusion or the small but constant and uncoordinated changes during a dynamic equilibrium? This agent-based model of a diffusion creates output that reveal insights for system stability.
This NetLogo model implements the Walk Away strategy in a spatial public goods game, where individuals have the ability to leave groups with insufficient levels of cooperation.
This spatially explicit agent-based model addresses how effective foraging radius (r_e) affects the effective size–and thus the equilibrium cultural diversity–of a structured population composed of central-place foraging groups.
A model of innovation diffusion in a structured population with two groups who are averse to adopting a produce popular with the outgroup.
The model combines the two elements of disorganization and motivation to explore their impact on teams. Effects of disorganization on team task performance (problem solving)
Reusing existing material stocks in developed built environments can significantly reduce the environmental footprint of the construction and demolition sector. However, material reuse in urban areas presents technical, temporal, and geographical challenges. Although a better understanding of spatial and temporal changes in material stocks could improve city resource management, limited scientific contributions have addressed this challenge.
This study details the steps followed in developing a spatially explicit rule-based simulation of materials stock. The simulation provides a proof of concept by incorporating the spatial and temporal dimensions of construction and demolition activities to analyse how various urban parameters determine material flows and embodied carbon in urban areas. The model explores the effects of 1) re-using recycled materials, 2) demolitions, 3) renovations and 4) various building typologies.
To showcase the model’s capabilities, the residential building stock of Gothenburg City is used as a case study, and eight building materials are tracked. Environmental impacts (A1-A3) are calculated with embodied carbon factors. The main parameters are explored in a baseline scenario. Then, a second scenario focuses on a hypothetical policy that promotes improvements in building energy performance.
The simulation can be expanded to include more materials and built environment assets and allows for future explorations on, for example, the role of logistics, the implementation of recycling or reuse stations, and, in general, supporting sustainable and circular strategies from the construction sector.
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