Computational Model Library

The Simulating Agroforestry Adoption in Rural Indonesia (SAFARI) model aims at exploring the adoption of illipe rubber agroforestry systems by farming households in the case study region in rural Indonesia. Thereby, the ABM simulates the interdependencies of agroforestry systems and local livelihoods, income, land use, biodiversity, and carbon fixation. The model contrasts development paths without agroforestry (business as usual (BAU) scenario), corresponding to a scenario where the government promotes rubber monoculture, with the introduction of illipe rubber agroforestry systems (IRA scenario) as an alternative. It aims to support policy-makers to assess the potential of IRA over larger temporal and spatial scales.

The SMASH model is an agent-based model of rural smallholder households. It models households’ evolving income and wealth, which they earn through crop sales. Wealth is carried in the form of livestock, which are grazed on an external rangeland (exogenous) and can be bought/sold as investment/coping mechanisms. The model includes a stylized representation of soil nutrient dynamics, modeling the inflows and outflows of organic and inorganic nitrogen from each household’s field.

The model has been applied to assess the resilience-enhancing effects of two different farm-level adaptation strategies: legume cover cropping and crop insurance. These two strategies interact with the model through different mechanims - legume cover cropping through ecological mechanisms and crop insurance through financial mechanisms. The model can be used to investigate the short- and long-term effects of these strategies, as well as how they may differently benefit different types of household.

Risk assessments are designed to measure cumulative risk and promotive factors for delinquency and recidivism, and are used by criminal and juvenile justice systems to inform sanctions and interventions. Yet, these risk assessments tend to focus on individual risk and often fail to capture each individual’s environmental risk. This agent-based model (ABM) explores the interaction of individual and environmental risk on the youth. The ABM is based on an interactional theory of delinquency and moves beyond more traditional statistical approaches used to study delinquency that tend to rely on point-in-time measures, and to focus on exploring the dynamics and processes that evolve from interactions between agents (i.e., youths) and their environments. Our ABM simulates a youth’s day, where they spend time in schools, their neighborhoods, and families. The youth has proclivities for engaging in prosocial or antisocial behaviors, and their environments have likelihoods of presenting prosocial or antisocial opportunities.

Peer reviewed Multilevel Group Selection I

Garry Sotnik Thaddeus Shannon Wayne W. Wakeland | Published Tue Apr 21 18:07:27 2020 | Last modified Sat Jul 3 20:38:55 2021

The Multilevel Group Selection I (MGS I) model simulates a population of contributing and non-contributing agents, competing on a social landscape for higher-value spots in an effort to withstand some selection pressure. It may be useful to both scientists and students in hypothesis testing, theory development, or more generally in understanding multilevel group selection.

Aqua.MORE

Lisa Huber Nico Bahro | Published Wed Nov 20 07:52:39 2019 | Last modified Sat Jul 3 07:19:28 2021

Aqua.MORE (Agent-based MOdelling of REsources in Socio-Hydrological Systems) is an agent based modelling (ABM) approach to simulate the resource flow and social interaction in a coupled natural and social system of water supply and demand. The model is able to simulate the two-way feedback as socio-economic agents influence the natural resource flow and the availability of this resource influences the agents in their behaviour.

Modeling Prejudice And Its Effect On Societal Prosperity

no contributors listed | Published Sun Jun 27 19:20:28 2021

Existing studies on prejudice, which is important in multi-group dynamics in societies, focus on the social-psychological knowledge behind the processes involving prejudice and its propagation. We instead create a multi-agent framework that simulates the propagation of prejudice and measures its tangible impact on the prosperity of individuals as well as of larger social structures, including groups and factions within. Groups in society help us define prejudice, and factions represent smaller tight-knit circles of individuals with similar opinions. We model social interactions using the Continuous Prisoner’s Dilemma (CPD) and a type of agent called a prejudiced agent, whose cooperation is affected by a prejudice attribute, updated over time based both on the agent’s own experiences and those of others in its faction. This model generates various results that both provide new insights into intergroup prejudice and its effects, as well as highlight and reinforce certain existing notions of prejudice.

This model is based on the Narragansett Bay, RI recreational fishery. The two types of agents are piscivorous fish and fishers (shore and boat fishers are separate “breeds”). Each time step represents one week. Open season is weeks 1-26, assuming fishing occurs during half the year. At each weekly time step, fish agents grow, reproduce, and die. Fisher agents decide whether or not to fish based on their current satisfaction level, and those that do go fishing attempt to catch a fish. If they are successful, they decide whether to keep or release the fish. In our publication, this model was linked to an Ecopath with Ecosim food web model where the commercial harvest of forage fish affected the biomass of piscivorous fish - which then became the starting number of piscivorous fish for this ABM. The number of fish caught in a season of this ABM was converted to a fishing pressure and input back into the food web model.

This model represents an agent-based social simulation for citizenship competences. In this model people interact by solving different conflicts and a conflict is solved or not considering two possible escenarios: when individual citizenship competences are considered and when not. In both cases the TKI conflict resolution styles are considered. Each conflict has associated a competence and the information about the conflicts and their competences is retrieved from an ontology which was developed in Protégé. To do so, a NetLogo extension was developed using the Java programming language and the JENA API (to make queries over the ontology).

Holmestrand School Model

Jessica Dimka | Published Fri Jun 18 20:09:15 2021

The Holmestrand model is an epidemiological agent-based model. Its aim is to test hypotheses related to how the social and physical environment of a residential school for children with disabilities might influence the spread of an infectious disease epidemic among students and staff. Annual reports for the Holmestrand School for the Deaf (Norway) are the primary sources of inspiration for the modeled school, with additional insights drawn from other archival records for schools for children with disabilities in early 20th century Norway and data sources for the 1918 influenza pandemic. The model environment consists of a simplified boarding school that includes residential spaces for students and staff, classrooms, a dining room, common room, and an outdoor area. Students and staff engage in activities reflecting hourly schedules suggested by school reports. By default, a random staff member is selected as the first case and is infected with disease. Subsequent transmission is determined by agent movement and interactions between susceptible and infectious pairs.

AgentEx aims to advance understanding of group processes for sustainable management of a common pool resource (CPR). By supporting the development and test explanations of cooperation and sustainable exploitation.

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