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.
Brain drain can be defined as the emigration of highly trained or qualified people from a particular country, which has many undesirable effects for the source country. Purpose of the model is to understand the dynamics of brain drain; and provide an initial version of a simulation-based decision support tool which can be used in discovering future trends for such emigration, and design effective social policies which can reduce, stop, or reverse the brain drain. The model proposes that skilled people would like to emigrate to maximise their utility, yet actual emigration is constrained with barriers, luck, and individuals’ social network.
The purpose of the model is to study the impact of global food trade on food and nutrition security in countries around the world. It will incorporate three main aspects of trade between countries, including a country’s wealth, geographic location, and its trade relationships with other countries (past and ongoing), and can be used to study food and nutrition security across countries in various scenarios, such as climate change, sustainable intensification, waste reduction and dietary change.
This model simulates the form and function of an idealised estuary with associated barrier-spit complex on the north east coast of New Zealand’s North Island (from Bream Bay to central Bay of Plenty) during the years 2010 - 2050 CE. It combines variables from social, ecological and geomorphic systems to simulate potential directions of change in shallow coastal systems in response to external forcing from land use, climate, pollution, population density, demographics, values and beliefs. The estuary is over 1000Ha, making it a large estuary according to Hume et al. (2007) - there are 12 large estuaries in the Auckland region alone (Suyadi et al., 2019). The model was developed as part of Andrew Allison’s PhD Thesis in Geography from the School of Environment and Institute of Marine Science, University of Auckland, New Zealand. The model setup allows for alteration of geomorphic, ecological and social variables to suit the specific conditions found in various estuaries along the north east coast of New Zealand’s North Island.
This model is not a predictive or forecasting model. It is designed to investigate potential directions of change in complex shallow coastal systems. This model must not be used for any purpose other than as a heuristic to facilitate researcher and stakeholder learning and for developing system understanding (as per Allison et al., 2018).
The purpose of this spatially-explicit agent-based model is to intervene in the debate about PES policy design, implementation and context. We use the case for a woodland-for-water payment for ecosystem services (PES) and model its implementation in a local area of Catalonia (NE Spain). The model is based on three sub-models. The structural contains four different designs of a PES policy. The social sub-model includes agent-based factors, by having four types of landowner categories managing or not the forests. This sub-model is based on behavioral studies and assumptions about reception and reaction to incentive policies from European-focused studies. The ecological sub-model is based on climate change data for the area. The output are the evolution of the ecological and social goals of the policy under different policy design scenarios. Our focus in Europe surges from the general context of land abandonment that many Mediterranean areas and Eastern countries are experiencing, and the growing interest from policy-makers and practitioners on the implementation of PES schemes to ameliorate this situation.
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.
In an associated paper which focuses on analyzing the structure of several egocentric networks of collective awareness platforms for sustainable innovation (CAPS), this model is developed. It answers the question whether the network structure is determinative for the sustainability of the created awareness. Based on a thorough literature review a model is developed to explain and operationalize the concept of sustainability of a social network in terms of importance, effectiveness and robustness. By developing this agent-based model, the expected outcomes after the dissolution of the CAPS are predicted and compared with the results of a network with the same participants but with different ties. Twitter data from different CAPS is collected and used to feed the simulation. The results show that the structure of the network is of key importance for its sustainability. With this knowledge and the ability to simulate the results after network changes have taken place, CAPS can assess the sustainability of their legacy and actively steer towards a longer lasting potential for social innovation. The retrieved knowledge urges organizations like the European Commission to adopt a more blended approach focusing not only on solving societal issues but on building a community to sustain the initiated development.
Our model allows simulating repeated conservation auctions in low-income countries. It is designed to assess policy-making by exploring the extent to which non-targeted repeated auctions can provide biodiversity conservation cost-effectively, while alleviating poverty. Targeting landholders in order to integrate both goals is claimed to be overambitious and underachieving because of the trade-offs they imply. The simulations offer insight on the possible outcomes that can derive from implementing conservation auctions in low-income countries, where landholders are likely to be risk averse and to face uncertainty.
This model is part of a JASSS article that introduce a conceptual framework for developing hybrid (system dynamics and agent-based) integrated assessment models, which focus on examining the human impacts on climate change. This novel modelling approach allows to reuse existing rigid, but well-established integrated assessment models, and adds more flexibility by replacing aggregate stocks with a community of vibrant interacting entities. The model provides a proof-of-concept of the application of this conceptual framework in form of an illustrative example. taking the settings of the US. It is solely created for the purpose of demonstrating our hybrid modelling approach; we do not claim that it has predictive powers.
In Western countries, the distribution of relative incomes within marriages tends to be skewed in a remarkable way. Husbands usually do not only earn more than their female partners, but there also is a striking discontinuity in their relative contributions to the household income at the 50/50 point: many wives contribute just a bit less than or as much as their husbands, but few contribute more. Our model makes it possible to study a social mechanism that might create this ‘cliff’: women and men differ in their incomes (even outside marriage) and this may differentially affect their abilities to find similar- or higher-income partners. This may ultimately contribute to inequalities within the households that form. The model and associated files make it possible to assess the merit of this mechanism in 27 European countries.
PowerGen-ABM is an optimisation model for power plant expansions from 2010 to 2025 with Indonesian electricity systems as the case study. PowerGen-ABM integrates three approaches: techno-economic analysis (TEA), linear programming (LP), and input-output analysis (IOA) and environmental analysis. TEA is based on the revenue requirement (RR) formula by UCDavis (2016), and the environmental analysis accounts for resource consumption (i.e., steel, concrete, aluminium, and energy) and carbon dioxide equivalent (CO2e) emissions during the construction and operational stages of power plants.