An agent-based model that simulates urban neighbourhoods. The model has been designed to simulate perceived livability and safety (PLS) of citizens. The score attached to perceived livability and safety, PLS, is the main output of the model and is the average of each individual’s PLS. These PLS scores, in turn, are specific to each citizen and highly dependent on their individual experiences. PLS is impacted by several different social factors: interactions with fellow citizens, police officers, and community workers; visiting or starting a neighbourhood initiative; experiencing a burglary; seeing a youth gang; or hearing from friends (of friends) about these events. On top of this, the model allows to set various types of social networks which also influence the PLS.

This is an interdisciplinary agent-based model with Monte Carlo simulations to assess the relative effects of broadcast and contagion processes in a multiplex social network. This multiplex approach models multiple channels of informal communication - phone, word-of-mouth, and social media - that vary in their attribute values. Each agent is an individual in a threatened community who, once warned, has a probability of warning others in their social network using one of these channels. The probability of an individual warning others is based on their warning source and the time remaining until disaster impact, among other variables. Default parameter values were chosen from empirical studies of disaster warnings along with the spatial aspects of Coos Bay, OR, USA and Seaside, OR, USA communities.

This model is intended to support oak tree management by representing the dynamics of oaks in multiple life stages and their competitors and consumers. This is implemented using a differential equation-based theoretical model representing three life stages of oaks: seedlings, juveniles, and adults. It includes the population dynamics of seedlings transitioning to juveniles, juveniles to adults, and adults producing new seedlings, as well as survival rates for each of the stages. It also includes a model of competition for light and water within seedlings and between seedlings and annual grasses. Finally, there is a predation term representing herbivores eating seedlings and grasses, using a Holling Type II (satiating) response with interference for predators and a death rate which depends on the resource extraction rate.

The code shared here accompanies the paper at https://doi.org/10.1371/journal.pone.0208451. It simulates the effects of various economic trade scenarios on the phenomenon of the ‘disappearing middle’ in the Scottish beef and dairy farming industries. The ‘disappearing middle’ is a situation in which there is a simultaneous observed decline in medium-sized enterprises and rise in the number of small and large-scale enterprises.

This generic agent-based model simulates the evolution of agent’s opinions through their exchange of arguments.
The idea behind this model is to explicitly represent the process of mental deliberation of agents from arguments to an opinion, through the use of Dung’s argumentation framework complemented by a structured description of arguments. An application of the model on the diffusion of vegetarian diets is proposed.

This is an empirical model described in http://dx.doi.org/10.1016/j.landurbplan.2010.05.001. The objective of the model is to simulate how the decision-making of farmers/agents with different strategies can affect the landscape structure in a region in the Netherlands.

Designed to capture the evolutionary forces of global society.

This models provides the infrastructure to model the activity of making. Individuals use resources they find in their environment plus those they buy, to design, construct and deconstruct items. It represents plans and complex objects explicitly.

This agent-based model, developed for the study “Online Protest and Repression in Authoritarian Settings,” examines how online protest and repression evolve in authoritarian contexts and how these dynamics affect ordinary users’ attitudes and behavior on social media. The model integrates key theoretical and empirical insights into social media use and core political factors that shape digital contention in authoritarian settings. The following questions are addressed: (1) how online protest–repression dynamics unfold across different levels of authoritarianism and varying compositions of committed accounts, and (2) how ordinary users’ internal propensity to protest and their perceived probability of successful repression change during online protest-repression contestation. The model is evaluated against two empirically grounded macro patterns observed in the real world. The first is enduring protest: online protest becomes dominant as vocal protesters grow to outnumber vocal repressors, shrinking the pool of silent users and stabilizing a pro-protest majority. The second is suppressed protest: online dissent is contained as vocal repression and silence expand in response to protest, yielding a sustained majority of repressive and silent accounts. Together, these dynamics demonstrate how dissenting voices are empowered and suppressed online in authoritarian settings.

The model demonstrates how non-instantaneous sampling techniques produce bias by overestimating the number of counted animals, when they move relative to the person counting them.