An agent based simple economy model that examines the effect of taxation and almsgiving (particularly Islamic almsgiving - zakat) for ameliorating wealth inequality.

The current rate of production and consumption of meat poses a problem both to peoples’ health and to the environment. This work aims to develop a simulation of peoples’ meat consumption behaviour in Britain using agent-based modelling. The agents represent individual consumers. The key variables that characterise agents include sex, age, monthly income, perception of the living cost, and concerns about the impact of meat on the environment, health, and animal welfare. A process of peer influence is modelled with respect to the agents’ concerns. Influence spreads across two eating networks (i.e. co-workers and household members) depending on the time of day, day of the week, and agents’ employment status. Data from a representative sample of British consumers is used to empirically ground the model. Different experiments are run simulating interventions of application of social marketing campaigns and a rise in price of meat. The main outcome is the average weekly consumption of meat per consumer. A secondary outcome is the likelihood of eating meat.

This model is developed as a theoretical agent-based model to study the general phenomena of network-based targeting strategies on eco-innovation adoption and diffusion through inter-firm networks.

SiFlo is an ABM dedicated to simulate flood events in urban areas. It considers the water flowing and the reaction of the inhabitants. The inhabitants would be able to perform different actions regarding the flood: protection (protect their house, their equipment and furniture…), evacuation (considering traffic model), get and give information (considering imperfect knowledge), etc. A special care was taken to model the inhabitant behavior: the inhabitants should be able to build complex reasoning, to have emotions, to follow or not instructions, to have incomplete knowledge about the flood, to interfere with other inhabitants, to find their way on the road network. The model integrates the closure of roads and the danger a flooded road can represent. Furthermore, it considers the state of the infrastructures and notably protection infrastructures as dyke. Then, it allows to simulate a dyke breaking.
The model intends to be generic and flexible whereas provide a fine geographic description of the case study. In this perspective, the model is able to directly import GIS data to reproduce any territory. The following sections expose the main elements of the model.

This model uses preference rankings w.r.t. ethnic group compositions (e.g. at companies) and assigns ethnic agents to groups based on their rankings.

Positive feedback can lead to “trapping” in local optima. Adding a simple negative feedback effect, based on ant behaviour, prevents this trapping

Models land-use, perception, and biocultural interactions between two forager populations.

Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.

An agent-based model of individual consumers making choices between five possible diets: omnivore, flexitarian, pescatarian, vegetarian, or vegan. Each consumer makes decisions based on personal constraints and values, and their perceptions of how well each diet matches with those values. Consumers can also be influenced by each other’s perceptions via interaction across three social networks: household members, friends, and acquaintances.

We employ this spatially explicit agent-based model to begin to examine how time-averaging can affect the spatial scale of cultural similarity in archaeological assemblage data. The model was built to address this question: to what extent does time-averaging affect the scale of local spatial association in the relative frequency of the most prevalent cultural variant in an archaeological landscape?