Our mission is to help computational modelers develop, document, and share their computational models in accordance with community standards and good open science and software engineering practices. Model authors can publish their model source code in the Computational Model Library with narrative documentation as well as metadata that supports open science and emerging norms that facilitate software citation, computational reproducibility / frictionless reuse, and interoperability. Model authors can also request private peer review of their computational models. Models that pass peer review receive a DOI once published.
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We also maintain a curated database of over 7500 publications of agent-based and individual based models with detailed metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
Displaying 10 of 239 results for "Curtis W Marean" clear search
The model simulates the national Campaign-Based Watershed Management program of Ethiopia. It includes three agents (farmers, Kebele/ village administrator, extension workers) and the physical environment that interact with each other. The physical environment is represented by patches (fields). Farmers make decisions on the locations of micro-watersheds to be developed, participation in campaign works to construct soil and water conservation structures, and maintenance of these structures. These decisions affect the physical environment or generate model outcomes. The model is developed to explore conditions that enhance outcomes of the program by analyzing the effect on the area of land covered and quality of soil and water conservation structures of (1) enhancing farmers awareness and motivation, (2) establishing and strengthening micro-watershed associations, (3) introducing alternative livelihood opportunities, and (4) enhancing the commitment of local government actors.
Explores how social networks affect implementation of institutional rules in a common pool resource.
We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.
We model interpersonal dynamics and study behavior in the classroom in the hypothetical case of a single teacher who defines students’ seating arrangements. The model incorporates the mechanisms of peer influence on study behavior, on attitude formation, and homophilous selection in order to depict the interrelated dynamics of networks, behavior, and attitudes. We compare various seating arrangement scenarios and observe how GPA distribution and level of prejudice changes over time.
Modeling an economy with stable macro signals, that works as a benchmark for studying the effects of the agent activities, e.g. extortion, at the service of the elaboration of public policies..
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MoPAgrIB model simulates the movement of cultivated patches in a savannah vegetation mosaic ; how they move and relocate through the landscape, depending on farming practices, population growth, social rules and vegetation growth.
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.
This model aims at creating agent populations that have “personalities”, as described by the Big Five Model of Personality. The expression of the Big Five in the agent population has the following properties, so that they resemble real life populations as closely as possible:
-The population mean of each trait is 0.5 on a scale from 0 to 1.
-The population-wide distribution of each trait approximates a normal distribution.
-The intercorrelations of the Big Five are close to those observed in the Literature.
The literature used to fit the model was a publication by Dimitri van der Linden, Jan te Nijenhuis, and Arnold B. Bakker:
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A Picit Jeu is an agent-based model (ABM) developed as a supporting tool for a role-playing game of the same name. The game is intended for stakeholders involved in land management and fire prevention at a municipality level. It involves four different roles: farmers, forest technicians, municipal administrators and forest private owners. The model aims to show the long-term effects of their different choices about forest and pasture management on fire hazard, letting them test different management strategies in an economically constraining context. It also allows the players to explore different climatic and economic scenarios. A Picit Jeu ABM reproduces the ecological, social and economic characteristics and dynamics of an Alpine valley in north-west Italy. The model should reproduce a primary general pattern: the less players undertake landscape management actions, by thinning and cutting forests or grazing pastures, the higher the probability that a fire will burn a large area of land.
This is a basic Susceptible, Infected, Recovered (SIR) model. This model explores the spread of disease in a space. In particular, it explores how changing assumptions about the number of susceptible people, starting number of infected people, as well as the disease’s infection probability, and average duration of infection. The model shows that the interactions of agents can drastically affect the results of the model.
We used it in our course on COVID-19: https://www.csats.psu.edu/science-of-covid19
Displaying 10 of 239 results for "Curtis W Marean" clear search