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.
LethalGeometry was developed to examine whether territory size influences the mortality risk for individuals within that territory. For animals who live in territoral groups and are lethally aggressive, we can expect that most aggression occurs along the periphery (or border) between two adjacent territories. For territories that are relatively large, the periphery makes up a proportionately small amount of the of the total territory size, suggesting that individuals in these territories might be less likely to die from these territorial skirmishes. LethalGeometry examines this geometric relationship between territory size and mortality risk under realistic assumptions of variable territory size and shape, variable border width, and stochastic interactions and movement.
The individuals (agents) are programmed to walk randomly about their environment, search for and eat food to obtain energy, reproduce if they can, and act aggressively toward individuals of other groups. During each simulation step, individuals analyze their environment and internal state to determine which actions to take. The actions available to individuals include moving, fighting, and giving birth.
B3GET simulates populations of virtual organisms evolving over generations, whose evolutionary outcomes reflect the selection pressures of their environment. The model simulates several factors considered important in biology, including life history trade-offs, investment in fighting ability and aggression, sperm competition, infanticide, and competition over access to food and mates. Downloaded materials include a starting genotype and population files. Edit the these files and see what changes occur in the behavior of virtual populations!
The model simulates interaction between internal physiological factors (e.g. energy balance) and external social factors (e.g. competition level) underlying feeding and social interaction behaviour of commercially group-housed pigs.
A proof-of-concept agent-based model ‘SimDrink’, which simulates a population of 18-25 year old heavy alcohol drinkers on a night out in Melbourne to provide a means for conducting policy experiments to inform policy decisions.