CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
this agent-based model explores the dynamics of volunteer participation in urban community gardens, by combining behavioral theory and institutional theory
This is an opinion dynamics model which extends the model found in (Martins 2009). The previous model had an unshared uncertainty assumption in agent-to-agent interaction this model relaxes that assumption. The model only supports a fully connect network where every agent has an equal likelihood of interacting with every other agent at any given time step. The model is highly modular so different social network paradigm can easier be implemented.
NetLogo model that allows scenarios concerning general social distancing, shielding of high-risk individuals, and informing contacts when symptomatic. Documentation includes a user manual with some simple scenarios, and technical information including descriptions of key procedures and parameter values.
1.7 billion people appear to be financially excluded. Due to the relevance of the problem, special purpose monies known as Complementary Currencies (CC) seem to be a potential solution. This doctoral project inquiries into the organising of money and its performative effects. It does so by following the communities designing CC and engineering their markets.
The fight against poverty is an urgent global challenge. Microinsurance is promoted as a valuable instrument for buffering income losses due to health or climate-related risks of low-income households in developing countries. However, apart from direct positive effects they can have unintended side effects when insured households lower their contribution to traditional arrangements where risk is shared through private monetary support.
RiskNetABM is an agent-based model that captures dynamics between income losses, insurance payments and informal risk-sharing. The model explicitly includes decisions about informal transfers. It can be used to assess the impact of insurance products and informal risk-sharing arrangements on the resilience of smallholders. Specifically, it allows to analyze whether and how economic needs (i.e. level of living costs) and characteristics of extreme events (i.e. frequency, intensity and type of shock) influence the ability of insurance and informal risk-sharing to buffer income shocks. Two types of behavior with regard to private monetary transfers are explicitly distinguished: (1) all households provide transfers whenever they can afford it and (2) insured households do not show solidarity with their uninsured peers.
The model is stylized and is not used to analyze a particular case study, but represents conditions from several regions with different risk contexts where informal risk-sharing networks between smallholder farmers are prevalent.
A generalized organizational agent- based model (ABM) containing both formal organizational hierarchy and informal social networks simulates organizational processes that occur over both formal network ties and informal networks.
Here we share the raw results of the social experiments of the paper “Gossip and competitive altruism support cooperation in a Public Good Game” by Giardini, Vilone, Sánchez, Antonioni, under review for Philosophical Transactions B. The experiment is thoroughly described there, in the following we summarize the main features of the experimental setup. The authors are available for further clarifications if requested.
Participants were recruited from the LINEEX subjects pool (University of Valencia Experimental Economics lab). 160 participants mean age = 21.7 years; 89 female) took part in this study in return for a flat payment of 5 EUR and the opportunity to earn an additional payment ranging from 8 to 16 EUR (mean total payment = 17.5 EUR). 80 subjects, divided into 5 groups of 16, took part in the competitive treatment while other 80 subjects participated in the non-competitive treatment. Laboratory experiments were conducted at LINEEX on September 16th and 17th, 2015.
NetPlop is a presentation editor built entirely in NetLogo, an agent-based modelling environment. The NetPlop Editor includes a variety of tools to design slide decks, and the Viewer allows these decks to be dis-played to an enraptured audience. A key feature of NetPlop is the ability to embed agent-based models. NetPlop was developed for SIGBOVIK 2021.
The Netlogo model is a conceptualization of the Moria refugee camp, capturing the household demographics of refugees in the camp, a theoretical friendship network based on values, and an abstraction of their daily activities. The model then simulates how Covid-19 could spread through the camp if one refugee is exposed to the virus, utilizing transmission probabilities and the stages of disease progression of Covid-19 from susceptible to exposed to asymptomatic / symptomatic to mild / severe to recovered from literature. The model also incorporates various interventions - PPE, lockdown, isolation of symptomatic refugees - to analyze how they could mitigate the spread of the virus through the camp.
This code is for an agent-based model of collective problem solving in which agents with different behavior strategies, explore the NK landscape while they communicate with their peers agents. This model is based on the famous work of Lazer, D., & Friedman, A. (2007), The network structure of exploration and exploitation.