Ants in the genus Temnothorax use tandem runs (rather than pheromone trails) to recruit to food sources. This model explores the collective consequences of this linear recruitment (as opposed to highly nonlinear pheromone trails).

The model represents an archetypical fishery in a co-evolutionary social-ecological environment, capturing different dimensions of trust between fishers and fish buyers for the establishment and persistence of self-governance arrangements.

This is based off my previous Profiler tutorial model, but with an added tutorial on converting it into a model usable with BehaviorSpace, and creating a BehaviorSpace experiment.

NeoCOOP is an iteration-based ABM that uses Reinforcement Learning and Artificial Evolution as adaptive-mechanisms to simulate the emergence of resource trading beliefs among Neolithic-inspired households.

WatASit is an agent-based model implemented in the CORMAS plateform. The model is developped to simulate irrigation situations at the operational level during a collective irrigation campaign.

This model implements two types of network diffusion from an initial group of activated nodes. In complex contagion, a node is activated if the proportion of neighbour nodes that are already activated exceeds a given threshold. This is intended to represented the spread of health behaviours. In simple contagion, an activated node has a given probability of activating its inactive neighbours and re-tests each time step until all of the neighbours are activated. This is intended to represent information spread.

A range of networks are included with the model from secondary school friendship networks. The proportion of nodes initially activated and the method of selecting those nodes are controlled by the user.

An agent model is presented that aims to capture the impact of cheap talk on collective action in a commons dilemma. The commons dilemma is represented as a spatially explicit renewable resource. Agent’s trust in others impacts the speed and harvesting rate, and trust is impacted by observed harvesting behavior and cheap talk. We calibrated the model using experimental data (DeCaro et al. 2021). The best fit to the data consists of a population with a small frequency of altruistic and selfish agents, and mostly conditional cooperative agents sensitive to inequality and cheap talk. This calibrated model provides an empirical test of the behavioral theory of collective action of Elinor Ostrom and Humanistic Rational Choice Theory.

This model is an abstract simulation of the COVID-19 virus in the United States population. It demonstrates how different masks of different types affect the progress of the virus.

The purpose of the model is to provide an analogy for how the Schwartz values may influence the aggregated economic performance, as measured by: public goods provision, private goods provision and leisure time.

This agent-based model simulates how new immigrant households choose where to live in Metro Vancouver under the origins diversity scenario. The model begins with 16,000 household agents, reflecting an expected annual population increase of about 42,500 people based on an average household size of 2.56. Each agent is assigned four characteristics: one of ten origin categories, income level (adjusted using NOC data and recent immigrant earnings), likelihood of having children, and preferred mode of commuting. The ten origin groups are drawn from Census patterns, including six subgroups within the broader Asian category (China, India, the Philippines, Iran, South Korea, and Other Asian countries) and two categories for immigrants from the Americas. This refined classification better captures the diversity of newcomers arriving in the region.