About the CoMSES Model Library more info
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 6 of 6 results ants clear search
Peer reviewed Ants Digging Networks
Elske van der Vaart | Published Friday, September 14, 2018This is a NetLogo version of Buhl et al.’s (2005) model of self-organised digging activity in ant colonies. It was built for a master’s course on self-organisation and its intended use is still educational. The ants’ behavior can easily be changed by toggling switches on the interface, or, for more advanced students, there is R code included allowing the model to be run and analysed through RNetLogo.
Ant Colony Optimization for infrastructure routing
P W Heijnen Emile Chappin Igor Nikolic | Published Wednesday, March 05, 2014 | Last modified Saturday, March 24, 2018The mode implements a variant of Ant Colony Optimization to explore routing on infrastructures through a landscape with forbidden zones, connecting multiple sinks to one source.
Linear recruitment leads to allocation and flexibility in collective foraging by ants
Zachary Joseph Shaffer Takao Sasaki Stephen Pratt | Published Thursday, July 11, 2013 | Last modified Thursday, September 05, 2013Ants in the genus Temnothorax use tandem runs (rather than pheromone trails) to recruit to food sources. This model explores the collective consequences of this linear recruitment (as opposed to highly nonlinear pheromone trails).
Composite Collective Decision Making - ant colony foraging model
Tomer Czaczkes Benjamin I Czaczkes | Published Thursday, December 17, 2015The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.
How to not get stuck – an ant model showing how negative feedback due to crowding maintains flexibility in ant foraging
Tomer Czaczkes | Published Thursday, December 17, 2015Positive feedback can lead to “trapping” in local optima. Adding a simple negative feedback effect, based on ant behaviour, prevents this trapping
Peer reviewed Umwelten Ants
Kit Martin | Published Thursday, January 15, 2015 | Last modified Thursday, August 27, 2015Simulates impacts of ants killing colony mates when in conflict with another nest. The murder rate is adjustable, and the environmental change is variable. The colonies employ social learning so knowledge diffusion proceeds if interactions occur.