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.
MELBIS-V1 is a spatially explicit agent-based model that allows the geospatial simulation of the decision-making process of newcomers arriving in the bilingual cities and boroughs of the island of Montreal, Quebec in CANADA, and the resulting urban segregation spatial patterns. The model was implemented in NetLogo, using geospatial raster datasets of 120m spatial resolution.
MELBIS-V2 enhances MELBIS-V1 to implement and simulate the decision-making processes of incoming immigrants, and to analyze the resulting spatial patterns of segregation as immigrants arrive and settle in various cities in Canada. The arrival and segregation of immigrants is modeled with MELBIS-V2 and compared for three major Canadian immigration gateways, including the City of Toronto, Metro Vancouver, and the City of Calgary.
This model is designed to address the following research question: How does the amount and topology of intergroup cultural transmission modulate the effect of local group extinction on selectively neutral cultural diversity in a geographically structured population? The experimental design varies group extinction rate, the amount of intergroup cultural transmission, and the topology of intergroup cultural transmission while measuring the effects of local group extinction on long-term cultural change and regional cultural differentiation in a constant-size, spatially structured population. The results show that for most of the intergroup social network topologies tested here, increasing the amount of intergroup cultural transmission (similar to increasing gene flow in a genetic model) erases the negative effect of local group extinction on selectively neutral cultural diversity. The stochastic (i.e., preference attachment) network seems to stand out as an exception.
Resilience of humans in the Upper Paleolithic could provide insights in how to defend against today’s environmental threats. Approximately 13,000 years ago, the Laacher See volcano located in present-day western Germany erupted cataclysmically. Archaeological evidence suggests that this is eruption – potentially against the background of a prolonged cold spell – led to considerable culture change, especially at some distance from the eruption (Riede, 2017). Spatially differentiated and ecologically mediated effects on contemporary social networks as well as social transmission effects mediated by demographic changes in the eruption’s wake have been proposed as factors that together may have led to, in particular, the loss of complex technologies such as the bow-and-arrow (Riede, 2014; Riede, 2009).
This model looks at the impact of the interaction between climate change trajectory and an extreme event, such as the Laacher See eruption, on the generational development of hunter-gatherer bands. Historic data is used to model the distribution and population dynamics of hunter-gatherer bands during these circumstances.
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.
This generic agent-based model simulates the evolution of agent’s opinions through their exchange of arguments.
The idea behind this model is to explicitly represent the process of mental deliberation of agents from arguments to an opinion, through the use of Dung’s argumentation framework complemented by a structured description of arguments. An application of the model on the diffusion of vegetarian diets is proposed.
This is an Agent Based Model of a generic food chain network consisting of stylized individuals representing producers, traders, and consumers. It is developed to: 1/ to describe the dynamically changing disaggregated flows of crop items between these agents, and 2/ to be able to explicitly consider agent behavior. The agents have implicit personal objectives for trading. Resilience and efficiency are quantified using the ascendency concept by linking these to the fraction of fulfillment of the overall explicit objective to have all consumers meet their food requirement. Different types of network structures in combination with different agent interaction types under different types of stylized shocks can be simulated.
The integrated and spatially-explicit ABM, called DIReC (Demography, Industry and Residential Choice), has been developed for Aberdeen City and the surrounding Aberdeenshire (Ge, Polhill, Craig, & Liu, 2018). The model includes demographic (individual and household) models, housing infrastructure and occupancy, neighbourhood quality and evolution, employment and labour market, business relocation, industrial structure, income distribution and macroeconomic indicators. DIReC includes a detailed spatial housing model, basing preference models on house attributes and multi-dimensional neighbourhood qualities (education, crime, employment etc.).
The dynamic ABM simulates the interactions between individuals, households, the labour market, businesses and services, neighbourhoods and economic structures. It is empirically grounded using multiple data sources, such as income and gender-age distribution across industries, neighbourhood attributes, business locations, and housing transactions. It has been used to study the impact of economic shocks and structural changes, such as the crash of oil price in 2014 (the Aberdeen economy heavily relies on the gas and oil sector) and the city’s transition from resource-based to a green economy (Ge, Polhill, Craig, & Liu, 2018).
The agent based model presented here is an explicit instantiation of the Two-Factor Theory (Herzberg et al., 1959) of worker satisfaction and dissatisfaction. By utilizing agent-based modeling, it allows users to test the empirically found variations on the Two-Factor Theory to test its application to specific industries or organizations.
Iasiello, C., Crooks, A.T. and Wittman, S. (2020), The Human Resource Management Parameter Experimentation Tool, 2020 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation, Washington DC.
While the world’s total urban population continues to grow, not all cities are witnessing such growth, some are actually shrinking. This shrinkage causes several problems to emerge including population loss, economic depression, vacant properties and the contraction of housing markets. Such problems challenge efforts to make cities sustainable. While there is a growing body of work on study shrinking cities, few explore such a phenomenon from the bottom up using dynamic computational models. To overcome this issue this paper presents an spatially explicit agent-based model stylized on the Detroit Tri-county area, an area witnessing shrinkage. Specifically, the model demonstrates how through the buying and selling of houses can lead to urban shrinkage from the bottom up. The model results indicate that along with the lower level housing transactions being captured, the aggregated level market conditions relating to urban shrinkage are also captured (i.e., the contraction of housing markets). As such, the paper demonstrates the potential of simulation to explore urban shrinkage and potentially offers a means to test polices to achieve urban sustainability.
TunaFisher ABM simulates the decisions of fishing companies and fishing vessels of the Philippine tuna purse seinery operating in the Celebes and Sulu Seas.
High fishing effort remains in many of the world’s fisheries, including the Philippine tuna purse seinery, despite a variety of policies that have been implemented to reduce it. These policies have predominantly focused on models of cause and effect which ignore the possibility that the intended outcomes are altered by social behavior of autonomous agents at lower scales.
This model is a spatially explicit Agent-based Model (ABM) for the Philippine tuna purse seine fishery, specifically designed to include social behavior and to study its effects on fishing effort, fish stock and industry profit. The model includes economic and social factors of decision making by companies and fishing vessels that have been informed by interviews.