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.
The aim of the model is to define when researcher’s assumptions of dependence or independence of cases in multiple case study research affect the results — hence, the understanding of these cases.
The model is designed to analyse the effects of mitigation measures on the European brown hare (Lepus europaeus), which is directly affected by ongoing land use change and has experienced widespread decline throughout Europe since the 1960s. As an input, we use two 4×4 km large model landscapes, which were generated by a landscape generator based on real field sizes and crop proportions and differed in average field size and crop composition. The crops grown annually are evaluated in terms of forage suitability, breeding suitability and crop richness for the hare. Six mitigation scenarios are implemented, defined by a 10 % increase in: (1) mixed silphie, (2) miscanthus, (3) grass-clover ley, (4) alfalfa, (5) set-aside, and (6) general crop richness. The model shows that that both landscape configuration and composition have a significant effect on hare population development, which responds particularly strongly to compositional changes.
This model simulates different seeding strategies for information diffusion in a social network adjusted to a case study area in rural Zambia. It systematically evaluates different criteria for seed selection (centrality measures and hierarchy), number of seeds, and interaction effects between seed selection criteria and set size.
Micro-targeted vs stochastic political campaigning agent-based model simulation. Written by Toby D. Pilditch (University of Oxford, University College London), in collaboration with Jens K. Madsen (University of Oxford, London School of Economics)
The purpose of the model is to explore the various impacts on voting intention among a population sample, when both stochastic (traditional) and Micto-targeted campaigns (MTCs) are in play. There are several stages of the model: initialization (setup), campaigning (active running protocols) and vote-casting (end of simulation). The campaigning stage consists of update cycles in which “voters” are targeted and “persuaded” - updating their beliefs in the campaign candidate / policies.
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!
Modeling an economy with stable macro signals, that works as a benchmark for studying the effects of the agent activities, e.g. extortion, at the service of the elaboration of public policies..
The MML is a hybrid modeling environment that couples an agent-based model of small-holder agropastoral households and a cellular landscape evolution model that simulates changes in erosion/deposition, soils, and vegetation.
MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.
MOOvPOP is designed to simulate population dynamics (abundance, sex-age composition and distribution in the landscape) of white-tailed deer (Odocoileus virginianus) for a selected sampling region.