A friendship game is a kind of network game: a game theory model on a network. This is a NetLogo model of an agent-based adaptation of “‘Friendship-based’ Games” by PJ Lamberson. The agents reach an equilibrium that depends on the strategy played and the topology of the network.

Overview

The Weather model is a procedural generation model designed to create realistic daily weather data for socioecological simulations. It generates synthetic weather time series for solar radiation, temperature, and precipitation using algorithms based on sinusoidal and double logistic functions. The model incorporates stochastic variation to mimic unpredictable weather patterns and aims to provide realistic yet flexible weather inputs for exploring diverse climate scenarios.

The Weather model can be used independently or integrated into larger models, providing realistic weather patterns without extensive coding or data collection. It can be customized to meet specific requirements, enabling users to gain a better understanding of the underlying mechanisms and have greater confidence in their applications.

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The FishCensus model simulates underwater visual census methods, where a diver estimates the abundance of fish. A separate model is used to shape species behaviours and save them to a file that can be shared and used by the counting model.

This is a tool to explore the effects of groups´ spatial segregation on the emergence of opinion polarization. It embeds two opinion formation models: a model of negative (and positive) social influence and a model of persuasive argument exchange.

MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.

MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.

This model was utilized for the simulation in the paper titled Effect of Network Homophily and Partisanship on Social Media to “Oil Spill” Polarizations. It allows you to examine whether oil spill polarization occurs through people’s communication under various conditions.

・Choose the network construction conditions you’d like to examine from the “rewire-style” chooser box.
・Select the desired strength of partisanship from the “partisanlevel” chooser box. You can also set the strength manually in the code tab.
・You can set the number of dynamic topics using the “number-of-topics” slider.
・Use the “divers-of-opinion” slider to set the number of preference types for each dynamic topic.
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In this simulation, we modify the norms game model to bid-rigging (collusion) model, while we can simulate also the norms game model.

This is an urban dynamics ABM of abstraction of a city and residents’ activities there.

It allows you to evaluate the effects of urban policies, such as an introduction of an open facility for residents with pedestrian-friendly accommodations, promotion of bicycle use, and control of private automobile use in an urban central area, in controlling urban sprawl.

The model of market of one commodity , in which there are in each moment of time the same quantity and the same quantity of money was formulated and researched in this text. We also study this system as a game of automata.

Schelling famously proposed an extremely simple but highly illustrative social mechanism to understand how strong ethnic segregation could arise in a world where individuals do not necessarily want it. Schelling’s simple computational model is the starting point for our extensions in which we build upon Wilensky’s original NetLogo implementation of this model. Our two NetLogo models can be best studied while reading our chapter “Agent-based Computational Models” (Flache and de Matos Fernandes, 2021). In the chapter, we propose 10 best practices to elucidate how agent-based models are a unique method for providing and analyzing formally precise, and empirically plausible mechanistic explanations of puzzling social phenomena, such as segregation, in the social world. Our chapter addresses in particular analytical sociologists who are new to ABMs.

In the first model (SegregationExtended), we build on Wilensky’s implementation of Schelling’s model which is available in NetLogo library (Wilensky, 1997). We considerably extend this model, allowing in particular to include larger neighborhoods and a population with four groups roughly resembling the ethnic composition of a contemporary large U.S. city. Further features added concern the possibility to include random noise, and the addition of a number of new outcome measures tuned to highlight macro-level implications of the segregation dynamics for different groups in the agent society.

In SegregationDiscreteChoice, we further modify the model incorporating in particular three new features: 1) heterogeneous preferences roughly based on empirical research categorizing agents into low, medium, and highly tolerant within each of the ethnic subgroups of the population, 2) we drop global thresholds (%-similar-wanted) and introduce instead a continuous individual-level single-peaked preference function for agents’ ideal neighborhood composition, and 3) we use a discrete choice model according to which agents probabilistically decide whether to move to a vacant spot or stay in the current spot by comparing the attractiveness of both locations based on the individual preference functions.

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