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.
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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.
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The model’s aim is to represent the price dynamics under very simple market conditions, given the values adopted by the user for the model parameters. We suppose the market of a financial asset contains agents on the hypothesis they have zero-intelligence. In each period, a certain amount of agents are randomly selected to participate to the market. Each of these agents decides, in a equiprobable way, between proposing to make a transaction (talk = 1) or not (talk = 0). Again in an equiprobable way, each participating agent decides to speak on the supply (ask) or the demand side (bid) of the market, and proposes a volume of assets, where this number is drawn randomly from a uniform distribution. The granularity depends on various factors, including market conventions, the type of assets or goods being traded, and regulatory requirements. In some markets, high granularity is essential to capture small price movements accurately, while in others, coarser granularity is sufficient due to the nature of the assets or goods being traded
Prior to COVID-19, female academics accounted for 45% of assistant professors, 37% of associate professors, and 21% of full professors in business schools (Morgan et al., 2021). The pandemic arguably widened this gender gap, but little systemic data exists to quantify it. Our study set out to answer two questions: (1) How much will the COVID-19 pandemic have impacted the gender gap in U.S. business school tenured and tenure-track faculty? and (2) How much will institutional policies designed to help faculty members during the pandemic have affected this gender gap? We used agent-based modeling coupled with archival data to develop a simulation of the tenure process in business schools in the U.S. and tested how institutional interventions would affect this gender gap. Our simulations demonstrated that the gender gap in U.S. business schools was on track to close but would need further interventions to reach equality (50% females). In the long-term picture, COVID-19 had a small impact on the gender gap, as did dependent care assistance and tenure extensions (unless only women received tenure extensions). Changing performance evaluation methods to better value teaching and service activities and increasing the proportion of female new hires would help close the gender gap faster.
This model simulates the behaviour of the agents in 3 wine markets parallel trading systems: Liv-ex, Auctions and additionally OTC market (finally not used). Behavioural aspects (impatience) is additionally modeled. This is an extention of parallel trading systems model with technical trading (momentum and contrarian) and noise trading.
The FishCensus model simulates underwater visual census methods, where a diver estimates the abundance of fish. A separate model is used to shape species behaviours and save them to a file that can be shared and used by the counting model.
Implementation of Milbrath’s (1965) model of political participation. Individual participation is determined by stimuli from the political environment, interpersonal interaction, as well as individual characteristics.
An agent-based framework that aggregates social network-level individual interactions to run targeting and rewarding programs for a freemium social app. Git source code in https://bitbucket.org/mchserrano/socialdynamicsfreemiumapps
The model presented here is extensively described in the paper ‘Talk less to strangers: How homophily can improve collective decision-making in diverse teams’ (forthcoming at JASSS). A full replication package reproducing all results presented in the paper is accessible at https://osf.io/76hfm/.
Narrative documentation includes a detailed description of the model, including a schematic figure and an extensive representation of the model in pseudocode.
The model develops a formal representation of a diverse work team facing a decision problem as implemented in the experimental setup of the hidden-profile paradigm. We implement a setup where a group seeks to identify the best out of a set of possible decision options. Individuals are equipped with different pieces of information that need to be combined to identify the best option. To this end, we assume a team of N agents. Each agent belongs to one of M groups where each group consists of agents who share a common identity.
The virtual teams in our model face a decision problem, in that the best option out of a set of J discrete options needs to be identified. Every team member forms her own belief about which decision option is best but is open to influence by other team members. Influence is implemented as a sequence of communication events. Agents choose an interaction partner according to homophily h and take turns in sharing an argument with an interaction partner. Every time an argument is emitted, the recipient updates her beliefs and tells her team what option she currently believes to be best. This influence process continues until all agents prefer the same option. This option is the team’s decision.
The Mobility Model is a model of a small-scale fishery with the purpose to study the movement of fishers between different sub-regions within a larger region, as they move between different regions to fish.
This is a model of the diffusion of alternative fuel vehicles based on manufacturer designs and consumer choices of those designs. It is written in Netlogo 4.0.3. Because it requires data to upload
Quality uncertainty and market failure: an interactive model to conduct classroom experiments
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