Our mission is to help computational modelers at all levels engage in the establishment and adoption of community standards and good practices for developing and sharing computational models. Model authors can freely publish their model source code in the Computational Model Library alongside narrative documentation, open science metadata, and other emerging open science norms that facilitate software citation, reproducibility, interoperability, and reuse. Model authors can also request peer review of their computational models to receive a DOI.
All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model publishing tutorial and contact us if you have any questions or concerns about publishing your model(s) in the Computational Model Library.
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.
Displaying 10 of 1083 results for "Bin-Tzong Chi" clear search
This model was developed as part of a class project, and explores the population dynamics and spread of an invasive insect, Emerald Ash Borer, in a county.
A draft model with some useful code for creating different network structures using the Netlogo NW extension. This model is used for the following tutorial:
Brughmans, T. (2018). Network structures and assembling code in Netlogo, Tutorial, https://archaeologicalnetworks.wordpress.com/resources/#structures .
This model incorporates three mechanisms shaping the dynamics of opinion formation, which mimics the dynamics of the virus spreading in the population. There are three methods of getting infected (or convinced) - direct contact, indirect contact, and contact with ``contaminated’’ elements.
This model is to explore the changes of paddy field landscape and household livelihood structure in the village under different policy scenarios, evaluate the eco-social effects of different policies, and provide decision support tools for proposing effective and feasible policies.
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.
IDEAL: Agent-Based Model of Residential Land Use Change where the choice of new residential development in based on the Ideal-point decision rule.
The model aims to simulate predator-prey relationships in an agricultural setting. The focus lies on avian communities and their effect on different pest organisms (here: pest birds, rodents, and arthropod pests). Since most case studies focused on the impact on arthropod pests (AP) alone, this model attempts to include effects on yield outcome. By incorporating three treatments with different factor levels (insectivorous bird species, falconry, nest box density) an experimental setup is given that allows for further statistical analysis to identify an optimal combination of the treatments.
In light of a global decline of birds, insects, and many other groups of organisms, alternative practices of pest management are heavily needed to reduce the input of pesticides. Avian pest control therefore poses an opportunity to bridge the disconnect between humans and nature by realizing ecosystem services and emphasizing sustainable social ecological systems.
The agent-based simulation of innovation diffusion is based on the idea of the Bass model (1969).
The adoption of an agent is driven two parameters: its innovativess p and its prospensity to conform with others. The model is designed for a computational experiment building up on the following four model variations:
(i) the agent population it fully connected and all agents share the same parameter values for p and q
(ii) the agent population it fully connected and agents are heterogeneous, i.e. individual parameter values are drawn from a normal distribution
(iii) the agents population is embeded in a social network and all agents share the same parameter values for p and q
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The model explores how two types of information - social (in the form of pheromone trails) and private (in the form of route memories) affect ant colony level foraging in a variable enviroment.
The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.
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