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 301 results for "Aaron C Fisher" clear search
Due to the role of education in promoting social status and facilitating upward social mobility, individuals and their families spare no effort to pursue better educational opportunities, especially in countries where education is highly competitive.
In China, the enrollment of senior high schools and universities mainly follows a ranking system based on students’ scores in national entrance exams (Zhongkao and Gaokao). Typically, students with higher scores have priority in choosing schools and endeavor to get into better senior high schools to increase their chances of entering a prestigious university.
However, students can only select “better” senior high schools based on their average Gaokao grades, which are strongly influenced by the initial performance (Zhongkao grades) of enrolled students. The true quality indicator of school education (schooling effect, defined as the grade improvement achieved through education at the senior high school) is unknowable. This raises the first question: will school rankings reflect the real educational quality of schools over decades of educational competition, or merely the initial quality of the students they enroll?
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(An empty output folder named “NETLOGOexperiment” in the same location with the LAKEOBS_MIX.nlogo file is required before the model can be run properly)
The model is motivated by regime shifts (i.e. abrupt and persistent transition) revealed in the previous paleoecological study of Taibai Lake. The aim of this model is to improve a general understanding of the mechanism of emergent nonlinear shifts in complex systems. Prelimnary calibration and validation is done against survey data in MLYB lakes. Dynamic population changes of function groups can be simulated and observed on the Netlogo interface.
Main functional groups in lake ecosystems were modelled as super-individuals in a space where they interact with each other. They are phytoplankton, zooplankton, submerged macrophyte, planktivorous fish, herbivorous fish and piscivorous fish. The relationships between these functional groups include predation (e.g. zooplankton-phytoplankton), competition (phytoplankton-macrophyte) and protection (macrophyte-zooplankton). Each individual has properties in size, mass, energy, and age as physiological variables and reproduce or die according to predefined criteria. A system dynamic model was integrated to simulate external drivers.
Set biological and environmental parameters using the green sliders first. If the data of simulation are to be logged, set “Logdata” as true and input the name of the file you want the spreadsheet(.csv) to be called. You will need create an empty folder called “NETLOGOexperiment” in the same level and location with the LAKEOBS_MIX.nlogo file. Press “setup” to initialise the system and “go” to start life cycles.
This agent-based model examines the impact of seasonal aggregation, dispersion, and learning opportunities on the richness and evenness of artifact styles under random social learning (unbiased transmission).
This ABM deals with commuting choices in the Italian city of Varese. Empirical data inform agents’ attitudes and modal choices costs and emissions. We evaluate ex ante the impact of policies for less polluting commuting choices.
In Western countries, the distribution of relative incomes within marriages tends to be skewed in a remarkable way. Husbands usually do not only earn more than their female partners, but there also is a striking discontinuity in their relative contributions to the household income at the 50/50 point: many wives contribute just a bit less than or as much as their husbands, but few contribute more. Our model makes it possible to study a social mechanism that might create this ‘cliff’: women and men differ in their incomes (even outside marriage) and this may differentially affect their abilities to find similar- or higher-income partners. This may ultimately contribute to inequalities within the households that form. The model and associated files make it possible to assess the merit of this mechanism in 27 European countries.
We consider scientific communities where each scientist employs one of two characteristic methods: an “adequate” method (A) and a “superior” method (S). The quality of methodology is relevant to the epistemic products of these scientists, and generate credit for their users. Higher-credit methods tend to be imitated, allowing to explore whether communities will adopt one method or the other. We use the model to examine the effects of (1) bias for existing methods, (2) competence to assess relative value of competing methods, and (3) two forms of interdisciplinarity: (a) the tendency for members of a scientific community to receive meaningful credit assignment from those outside their community, and (b) the tendency to consider new methods used outside their community. The model can be used to show how interdisciplinarity can overcome the effects of bias and incompetence for the spread of superior methods.
This model system aims to simulate the whole process of task allocation, task execution and evaluation in the team system through a feasible method. On the basis of Complex Adaptive Systems (CAS) theory and Agent-based Modelling (ABM) technologies and tools, this simulation system attempts to abstract real-world teams into MAS models. The author designs various task allocation strategies according to different perspectives, and the interaction among members is concerned during the task-performing process. Additionally, knowledge can be acquired by such an interaction process if members encounter tasks they cannot handle directly. An artificial computational team is constructed through ABM in this simulation system, to replace real teams and carry out computational experiments. In all, this model system has great potential for studying team dynamics, and model explorers are encouraged to expand on this to develop richer models for research.
This model takes concepts from a JASSS paper this is accepted for the October, 2023 edition and applies the concepts to empirical data from counties surrounding and including Cleveland Ohio. The agent-based model has a proportional number of agents in each of the counties to represent the correct proportions of adults in these counties. The adoption decision probability uses the equations from Bass (1969) as adapted by Rand & Rust (2011). It also includes the Outgroup aversion factor from Smaldino, who initially had used a different imitation model on line grid. This model uses preferential attachment network as a metaphor for social networks influencing adoption. The preferential network can be adjusted in the model to be created based on both nodes preferred due to higher rank as well as a mild preference for nodes of a like group.
How can a strictly egalitarian social system give way to a stratified society if all of its members punish each other for any type of selfish behavior? This model examines the role of prestige bias in constant and variable environments on the development of hierarchies of wealth.
This version of the accumulated copying error (ACE) model is designed to address the following research question: how does finite population size (N) affect the coefficient of variation (CV) of a continuous cultural trait under the assumptions that the only source of copying error is visual perception error and that the continuous trait can take any positive value (i.e., it has no upper bound)? The model allows one to address this question while assuming the continuous trait is transmitted via vertical transmission, unbiased transmission, prestige biased transmission, mean conformist transmission, or median conformist transmission. By varying the parameter, p, one can also investigate the effect of population size under a mix of vertical and non-vertical transmission, whereby on average (1-p)N individuals learn via vertical transmission and pN individuals learn via either unbiased transmission, prestige biased transmission, mean conformist transmission, or median conformist transmission.
Displaying 10 of 301 results for "Aaron C Fisher" clear search