CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
The modeling includes citizens, bounded into families; firms and governments; all of them interacting in markets for goods, labor and real estate. The model is spatial and dynamic.
The purpose of the model presented by Glance et al is to study the ‘contribute vs. free-ride’ dilemma present in organizations.
This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.
The DITCH model has been developed to investigate partner selection processes, focusing on individual preferences, opportunities for contact, and group size to uncover how these may lead to differential rates of inter-ethnic marriage.
This model illustrates a positive ‘transport’ feedback loop in which lines with different resistance to flows of material result in variation in rates of change in linked entities.
This Repast Simphony model simulates genomic admixture during the farming expansion of human groups from mainland Asia into the Papuan dominated islands of Southeast Asia during the Neolithic period.
Default Initial skill, read ODD for more info. The purpose of the model presented by Salau is to study the ’player profit vs. club benefit’ dilemma present in professional soccer organizations.
This model explores the effects of agent interaction, information feedback, and adaptive learning in repeated auctions for farmland. It gathers information for three types of sealed-bid auctions, and one English auction and compares the auctions on the basis of several measures, including efficiency, price information revelation, and ability to handle repeated bidding and agent learning.
This model is a market game for evaluating the effectiveness of the UK government’s 2008-2010 policy on promoting smart metering in the UK retail electricity market. We break down the policy into four
Next generation of the CHALMS model applied to a coastal setting to investigate the effects of subjective risk perception and salience decision-making on adaptive behavior by residents.