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We also maintain a curated database of over 7500 publications of agent-based and individual based models with additional detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
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Juan Castilla-Rho et al. (2015) developed a platform, named FLowLogo, which integrates a 2D, finite-difference solution of the governing equations of groundwater flow with agent-based simulation. We used this model for Rafsanjan Aquifer, which is located in an arid region in Iran. To use FLowLogo for a real case study, one needs to add GIS shapefiles of boundary conditions and modify the code written in NetLogo a little bit. The FlowLogo model used in our research is presented here.
The purpose of the model is to study the impact of global food trade on food and nutrition security in countries around the world. It will incorporate three main aspects of trade between countries, including a country’s wealth, geographic location, and its trade relationships with other countries (past and ongoing), and can be used to study food and nutrition security across countries in various scenarios, such as climate change, sustainable intensification, waste reduction and dietary change.
Inspired by the European project called GLODERS that thoroughly analyzed the dynamics of extortive systems, Bottom-up Adaptive Macroeconomics with Extortion (BAMERS) is a model to study the effect of extortion on macroeconomic aggregates through simulation. This methodology is adequate to cope with the scarce data associated to the hidden nature of extortion, which difficults analytical approaches. As a first approximation, a generic economy with healthy macroeconomics signals is modeled and validated, i.e., moderate inflation, as well as a reasonable unemployment rate are warranteed. Such economy is used to study the effect of extortion in such signals. It is worth mentioning that, as far as is known, there is no work that analyzes the effects of extortion on macroeconomic indicators from an agent-based perspective. Our results show that there is significant effects on some macroeconomics indicators, in particular, propensity to consume has a direct linear relationship with extortion, indicating that people become poorer, which impacts both the Gini Index and inflation. The GDP shows a marked contraction with the slightest presence of extortion in the economic system.
This is the model for a paper that is based on a simulation model, programmed in Netlogo, that demonstrates changes in market structure that occur as marginal costs, demand, and barriers to entry change. Students predict and observe market structure changes in terms of number of firms, market concentration, market price and quantity, and average marginal costs, profits, and markups across the market as firms innovate. By adjusting the demand growth and barriers to entry, students can […]
This agent-based model represents a stylized inter-organizational innovation network where firms collaborate with each other in order to generate novel organizational knowledge.
Agent-based version of the simple search and barter economy conceived by Peter Diamond in 1982. The model is also known as Coconut Model.
An artifcal stock market model that allows users to vary the number of risky assets as well as the network topology that investors forms in an attempt to understand the dynamics of the market.
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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This is a generic sub-model of animal territory formation. It is meant to be a reusable building block, but not in the plug-and-play sense, as amendments are likely to be needed depending on the species and region. The sub-model comprises a grid of cells, reprenting the landscape. Each cell has a “quality” value, which quantifies the amount of resources provided for a territory owner, for example a tiger. “Quality” could be prey density, shelter, or just space. Animals are located randomly in the landscape and add grid cells to their intial cell until the sum of the quality of all their cells meets their needs. If a potential new cell to be added is owned by another animal, competition takes place. The quality values are static, and the model does not include demography, i.e. mortality, mating, reproduction. Also, movement within a territory is not represented.
The DITCH model has been developed to investigate partner selection processes, focusing on individual preferences, opportunities for contact, and group size to uncover how these may lead to differential rates of inter-ethnic marriage.
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