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.

This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.

This theoretical model includes forested polygons and three types of agents: forest landowners, foresters, and peer leaders. Agent rules and characteristics were parameterized from existing literature and an empirical survey of forest landowners.

Captures interplay between fixed ethnic markers and culturally evolved tags in the evolution of cooperation and ethnocentrism. Agents evolve cultural tags, behavioural game strategies and in-group definitions. Ethnic markers are fixed.

This adaptation of the Relative Agreement model of opinion dynamics (Deffuant et al. 2002) extends the Meadows and Cliff (2012) implementation of this model in a manner that explores the effect of the network structure among the agents.

This NetLogo model simulates trait-based biotic responses to climate change in an environmentally heterogeneous continent in an evolving clade, the species of which are each represented by local populations that disperse and interbreed; they also are subject to selection, genetic drift, and local extirpation. We simulated mammalian herbivores, whose success depends on tooth crown height, vegetation type, precipitation and grit. This model investigates the role of dispersal, selection, extirpation, and other factors contribute to resilience under three climate change scenarios.

The purpose of this agent-based model is to explore the emergent phenomena associated with scientific publication, including quantity and quality, from different academic types based on their publication strategies.

The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.

We developed an agent-based model to explore underlying mechanisms of behavioral clustering that we observed in human online shopping experiments.

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.