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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Digital-Twin model of Sejong City – Source model code & data
We only shared model codes, excluding private data and simulation engine codes.
The followings are brief reasons for the items we cannot share.
Agent-based models of organizational search have long investigated how exploitative and exploratory behaviors shape and affect performance on complex landscapes. To explore this further, we build a series of models where agents have different levels of expertise and cognitive capabilities, so they must rely on each other’s knowledge to navigate the landscape. Model A investigates performance results for efficient and inefficient networks. Building on Model B, it adds individual-level cognitive diversity and interaction based on knowledge similarity. Model C then explores the performance implications of coordination spaces. Results show that totally connected networks outperform both hierarchical and clustered network structures when there are clear signals to detect neighbor performance. However, this pattern is reversed when agents must rely on experiential search and follow a path-dependent exploration pattern.
The purpose of this curricular model is to teach students the basics of modeling complex systems using agent-based modeling. It is a simple SIR model that simulates how a disease spreads through a population as its members change from susceptible to infected to recovered and then back to susceptible. The dynamics of the model are such that there are multiple emergent outcomes depending on the parameter settings, initial conditions, and chance.
The curricular model can be used with the chapter Agent-Based Modeling in Mixed Methods Research (Moritz et al. 2022) in the Handbook of Teaching Qualitative & Mixed Methods (Ruth et al. 2022).
The instructional videos can be accessed on YouTube: Video 1 (https://youtu.be/32_JIfBodWs); Video 2 (https://youtu.be/0PK_zVKNcp8); and Video 3 (https://youtu.be/0bT0_mYSAJ8).
Industrial clustering patterns are the result of an entrepreneurial process where spinoffs inherit the ideas and attributes of their parent firms. This computational model maps these patterns using abstract methodologies.
PSoup is an educational program in which evolution is demonstrated, on the desk-top, as you watch. Blind bugs evolve sophisticated heuristic search algorithms to be the best at finding food fast.
In CmLab we explore the implications of the phenomenon of Conservation of Money in a modern economy. This is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.
The publication and mathematical model upon which this ABM is based shows one mechanism that can lead to stable behavioral and cultural traits between groups.
We reconstruct Cohen, March and Olsen’s Garbage Can model of organizational choice as an agent-based model. We add another means for avoiding making decisions: buck-passing difficult problems to colleagues.
The purpose of the model is to examine whether and how mobile pastoralists are able to achieve an Ideal Free Distribution (IFD).
IDEAL: Agent-Based Model of Residential Land Use Change where the choice of new residential development in based on the Ideal-point decision rule.
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