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.
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The Groundwater Commons Game synthesises and extends existing work on human cooperation and collective action, to elucidate possible determinants and pathways to regulatory compliance in groundwater systems globally.
A road freight transport (RFT) operation involves the participation of several types of companies in its execution. The TRANSOPE model simulates the subcontracting process between 3 types of companies: Freight Forwarders (FF), Transport Companies (TC) and self-employed carriers (CA). These companies (agents) form transport outsourcing chains (TOCs) by making decisions based on supplier selection criteria and transaction acceptance criteria. Through their participation in TOCs, companies are able to learn and exchange information, so that knowledge becomes another important factor in new collaborations. The model can replicate multiple subcontracting situations at a local and regional geographic level.
The succession of n operations over d days provides two types of results: 1) Social Complex Networks, and 2) Spatial knowledge accumulation environments. The combination of these results is used to identify the emergence of new logistics clusters. The types of actors involved as well as the variables and parameters used have their justification in a survey of transport experts and in the existing literature on the subject.
As a result of a preferential selection process, the distribution of activity among agents shows to be highly uneven. The cumulative network resulting from the self-organisation of the system suggests a structure similar to scale-free networks (Albert & Barabási, 2001). In this sense, new agents join the network according to the needs of the market. Similarly, the network of preferential relationships persists over time. Here, knowledge transfer plays a key role in the assignment of central connector roles, whose participation in the outsourcing network is even more decisive in situations of scarcity of transport contracts.
Disparities in access to primary health care have led to health disadvantages among Latinos and other non-White racial groups. To better identify and understand which policies are most likely to improve health care for Latinos, we examined differences in access to primary care between Latinos with proficient English language skills and Latinos with limited English proficiency (LEP) and estimated the extent of access to primary care providers (PCPs) among Latinos in the U.S.
This agent-based model explores the existence of positive feedback loops related to illegal, unregulated, unreported (IUU) fishing; the use of forced labor; and the depletion of fish populations due to commercial fishing.
We compare three model estimates for the time and treatment requirements to eliminate HCV among HIV-positive MSM in Victoria, Australia: a compartmental model; an ABM parametrized by surveillance data; and an ABM with a more heterogeneous population.
This model describes and analyses the Travel-Tour Case study.
This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.
Exploring how learning and social-ecological networks influence management choice set and their ability to increase the likelihood of species coexistence (i.e. biodiversity) on a fragmented landscape controlled by different managers.
The purpose of this model is to understand the role of trade networks and their interaction with different fish resources, for fish provision. The model is developed based on a multi-methods approach, combining agent-based modeling, network analysis and qualitative data based on a small-scale fisheries study case. The model can be used to investigate both how trade network structures are embedded in a social-ecological context and the trade processes that occur within them, to analyze how they lead to emergent outcomes related to the resilience of fish provision. The model processes are informed by qualitative data analysis, and the social network analysis of an empirical fish trade network. The network analysis can be used to investigate diverse network structures to perform model experiments, and their influence on model outcomes.
The main outcomes we study are 1) the overexploitation of fish resources and 2) the availability and variability of fish provision to satisfy different market demands, and 3) individual traders’ fish supply at the micro-level. The model has two types of trader agents, seller and dealer. The model reveals that the characteristics of the trade networks, linked to different trader types (that have different roles in those networks), can affect the resilience of fish provision.
This model replicates the Axelrod prisoner’s dilemma tournaments. The model takes as input a file of strategies and pits them against each other to see who achieves the best payoff in the end. Change the payoff structure to see how it changes the tournament outcome!
Displaying 10 of 138 results for "Reginald Lee Hayes" clear search