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.
Displaying 10 of 224 results for "Nick Glover" clear search
Butterflies (turtles) goes through metamorphism and moves to corresponding patches each season of the year. The number of years and seasons are monitored.
Contains python3 code used to replicate the culture model from the JASSS submission: “Modeling Cultural Dissemination and Divergence between Rural and Urban Regions.”
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.
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.
CINCH1 (Covid-19 INfection Control in Hospitals), is a prototype model of physical distancing for infection control among staff in University College London Hospital during the Covid-19 pandemic, developed at the University of Leeds, School of Geography. It models the movement of collections of agents in simple spaces under conflicting motivations of reaching their destination, maintaining physical distance from each other, and walking together with a companion. The model incorporates aspects of the Capability, Opportunity and Motivation of Behaviour (COM-B) Behaviour Change Framework developed at University College London Centre for Behaviour Change, and is aimed at informing decisions about behavioural interventions in hospital and other workplace settings during this and possible future outbreaks of highly contagious diseases. CINCH1 was developed as part of the SAFER (SARS-CoV-2 Acquisition in Frontline Health Care Workers – Evaluation to Inform Response) project
(https://www.ucl.ac.uk/behaviour-change/research/safer-sars-cov-2-acquisition-frontline-health-care-workers-evaluation-inform-response), funded by the UK Medical Research Council. It is written in Python 3.8, and built upon Mesa version 0.8.7 (copyright 2020 Project Mesa Team).
This model looks at implications of author/referee interaction for quality and efficiency of peer review. It allows to investigate the importance of various reciprocity motives to ensure cooperation. Peer review is modelled as a process based on knowledge asymmetries and subject to evaluation bias. The model includes various simulation scenarios to test different interaction conditions and author and referee behaviour and various indexes that measure quality and efficiency of evaluation […]
The model simulates flood damages and its propagation through a cooperative, productive, farming system, characterized as a star-type network, where all elements in the system are connected one to each other through a central element.
This project attempts to model how social media platforms recommend a user followers based on their interests, and how those individual interests change as a result of the influences from those they follow/are followed by.
We have three types of users on the platform:
Consumers (🔴), who update their interests based on who they’re following.
Creators (⬛), who update their interests based on who’s following them.
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This ABM looks at the effect of multiple reviewers and their behavior on the quality and efficiency of peer review. It models a community of scientists who alternatively act as “author” or “reviewer” at each turn.
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