Emulation is one of the simplest and most common mechanisms of social interaction. In this paper we introduce a descriptive computational model that attempts to capture the underlying dynamics of social processes led by emulation.

Designed to capture the evolutionary forces of global society.

The purpose of this model is to better understand the dynamics of a multihost pathogen in two host system comprising of high densities of domestic hosts and sympatric wildlife hosts susceptible to the pathogen.

The purpose of the OMOLAND-CA is to investigate the adaptive capacity of rural households in the South Omo zone of Ethiopia with respect to variation in climate, socioeconomic factors, and land-use at the local level.

This model, realized on the NetLogo platform, compares utility levels at home and abroad to simulate agents’ migration and their eventual return. Our model is based on two fundamental individual features, i.e. risk aversion and initial expectation, which characterize the dynamics of different agents according to the evolution of their social contacts.

Signaling chains are a special case of Lewis’ signaling games on networks. In a signaling chain, a sender tries to send a single unit of information to a receiver through a chain of players that do not share a common signaling system.

We develop an agent-based model (U-TRANS) to simulate the transition of an abstract city under an industrial revolution. By coupling the labour and housing markets, we propose a holistic framework that incorporates the key interacting factors and micro processes during the transition. Using U-TRANS, we look at five urban transition scenarios: collapse, weak recovery, transition, enhanced training and global recruit, and find the model is able to generate patterns observed in the real world. For example, We find that poor neighbourhoods benefit the most from growth in the new industry, whereas the rich neighbourhoods do better than the rest when the growth is slow or the situation deteriorates. We also find a (subtle) trade-off between growth and equality. The strategy to recruit a large number of skilled workers globally will lead to higher growth in GDP, population and human capital, but it will also entail higher inequality and market volatility, and potentially create a divide between the local and international workers. The holistic framework developed in this paper will help us better understand urban transition and detect early signals in the process. It can also be used as a test-bed for policy and growth strategies to help a city during a major economic and technological revolution.

The model implements a double auction financial markets with two types of agents: rational and noise. The model aims to study the impact of different compensation structure on the market stability and market quantities as prices, volumes, spreads.

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.

This spatially explicit agent-based model addresses how effective foraging radius (r_e) affects the effective size–and thus the equilibrium cultural diversity–of a structured population composed of central-place foraging groups.