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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A more complete description of the model can be found in Appendix I as an ODD protocol. This model is an expansion of the Hemelrijk (1996) that was expanded to include a simple food seeking behavior.
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.
This NetLogo model simulates how coral reefs around the islands of Palau would develop under different emission scenarios and with selected adaptation strategies. Reef health is indicated by coral cover (%) and is affected by four major climate change impacts: increasing sea surface temperature, sea level rise, ocean acidification, and more intense typhoons. The model differentiates between inner and outer reefs, with the former naturally adapted to warmer, more acidic waters. The simulation includes bleaching events and possible recovery. In addition, the user can choose between different coral transplantation strategies as well as regulate natural thermal adaptation rates.
Software for an agent-based game-theoretic model of the contact hypothesis of prejudice reduction, to accompany “Modeling Prejudice Reduction,” in the Handbook of Computational Social Psychology, adapted from Public Affairs Quarterly 19 (2) 2005.
The Agent-Based Wildfire Simulation Environment (ABWiSE) translates the concept of a moving fire front as a set of mobile fire agents that respond to, and interact with, vegetation, wind, and terrain. Presently, the purpose of ABWiSE is to explore how ABM, using simple interactions between agents and a simple atmospheric feedback model, can simulate emergent fire spread patterns.
The model objective’s is to explore the management choice set to uncover which subsets of strategies are most effective at maximizing species coexistence on a fragmented landscape.
The purpose of the model is to generate coalition structures of different glove games, using a specially designed algorithm. The coalition structures can be are later analyzed by comparing them to core partitions of the game used. Core partitions are coalition structures where no subset of players has an incentive to form a new coalition.
The algorithm used in this model is an advancement of the algorithm found in Collins & Frydenlund (2018). It was used used to generate the results in Vernon-Bido & Collins (2021).
This model illustrates actor interaction in the construction sector, according to information gathered in NL. It offers a simple frame to represent diverse interests, interdependencies and effects on the number of built sustainable houses.
The Groundwater Commons Game synthesises and extends existing work on human cooperation and collective action, to elucidate possible determinants and pathways to regulatory compliance in groundwater systems globally.
We present an agent-based model that maps out and simulates the processes by which individuals within ecological restoration organizations communicate and collectively make restoration decisions.
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