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.
Please check out our model archive tutorial or contact us if you have any questions or concerns about archiving your model.
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.
We extend the Flache-Mäs model to incorporate the location and dyadic communication regime of the agents in the opinion formation process. We make spatially proximate agents more likely to interact with each other in a pairwise communication regime.
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. This code corresponds to equations 1-70 given in the paper “A Mathematical Model of The Beer Game”.
The simulation model LAMDA investigates the influences of varying cognitive abilities of the decision maker on the truth-inducing effect of the Groves mechanism. Bounded rationality concepts are represented by information states and learning models.
This is an agent-based model of the implementation of the self-enforcing agreement in cooperative teams.
Model for evaluating various ambulance dispatching policies of an equity constrained emergency medical services under bounded rationality.
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.
Its a multi agent simulation environment, provided using JADE/Java. It gets the number of agents and tasks, then divides the physical environment to some segments, and then runs a greedy capability-based coalition formation and task allocation algorithm to assign tasks to groups of agents and complete the tasks.
This model simulates networking mechanisms of an empirical social network. It correlates event determinants with place-based geography and social capital production.
The purpose of this model is to explore the effects of different power structures on a cross-functional team’s prosocial decision making. Are certain power distributions more conducive to the team making prosocial decisions?
This is the R code of the mathematical model that includes the decision making formulations for artificial agents. Plus, the code for graphical output is also added to the original code.