Agent-based modeling and simulation (ABMS) is a class of computational models for simulating the actions and interactions of autonomous agents with the goal of assessing their effects on a system as a whole. Several frameworks for generating parallel ABMS applications have been developed taking advantage of their common characteristics, but there is a lack of a general benchmark for comparing the performance of generated applications. We propose and design a benchmark that takes into consideration the most common characteristics of this type of applications and includes parameters for influencing their relevant performance aspects. We provide an initial implementation of the benchmark for FLAME one of the most popular parallel ABMS platforms, and we use it for comparing the applications generated by these platforms.

The purpose of this model is to study effect of a particular kind of spatial externality, “fashion effect”, on the dynamics of technology diffusion among rational adopters with uncertainty about the p

SimAdapt: An individual-based genetic model for simulating landscape management impacts on populations

The purpose of the model is to simulate the future growth of human settlements in the Nile river valley in Egypt. The model contains processes to mimic spatial patterns found in the case study region.

This is a re-implementation of the model described in Gilbert, Nigel. (1997). A simulation of the structure of academic science. Sociological Research Online, 2(2)3, http://www.socresonline.org.uk/

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.

Contains python3 code to replicate the opinion dynamics model from our (so far unpublished) JASSS sumbission “A Balance Model of Opinion Hyperpolarization”. The main function is run_model(), which returns a dictionary object containing various outcome metrics.

This model investigates the link between prescribed growth in body size, population dynamics and density dependence through population feedback on available resources.

The simulation model conducts fine-grained population projection by specifying life course dynamics of individuals and couples by means of traditional demographic microsimulation and by using agent-based modeling for mate matching.

What is stable: the large but coordinated change during a diffusion or the small but constant and uncoordinated changes during a dynamic equilibrium? This agent-based model of a diffusion creates output that reveal insights for system stability.