This model simulates the emergence of a dual market structure from firm-level interaction. Firms are profit-seeking, and demand is represented by a unimodal distribution of consumers along a set of taste positions.

This model explores a social mechanism that links the reversal of the gender gap in education with changing patterns in relative divorce risks in 12 European countries.

This generic model simulates climate change adaptation in the form of resistance, accommodation, and retreat in coastal regions vulnerable to sea level rise and flooding. It tracks how population changes as households retreat to higher ground.

RaMDry allows to study the dynamic use of forage ressources by herbivores in semi-arid savanna with an emphasis on effects of change of climate and management. Seasonal dynamics affects the amount and the nutritional values of the available forage.

This model has been created with and for the researcher-farmers of the Muonde Trust (http://www.muonde.org/), a registered Zimbabwean non-governmental organization dedicated to fostering indigenous innovation. Model behaviors and parameters (mashandiro nemisiyano nedzimwe model) derive from a combination of literature review and the collected datasets from Muonde’s long-term (over 30 years) community-based research. The goals of this model are three-fold (muzvikamu zvitatu):
A) To represent three components of a Zimbabwean agro-pastoral system (crops, woodland grazing area, and livestock) along with their key interactions and feedbacks and some of the human management decisions that may affect these components and their interactions.
B) To assess how climate variation (implemented in several different ways) and human management may affect the sustainability of the system as measured by the continued provisioning of crops, livestock, and woodland grazing area.
C) To provide a discussion tool for the community and local leaders to explore different management strategies for the agro-pastoral system (hwaro/nzira yekudyidzana kwavanhu, zvipfuo nezvirimwa), particularly in the face of climate change.

Migration or other long-distance movement into other regions is a common strategy of fishers and fishworkers living and working on the coast to adapt to environmental change. This model attempts to understand the general dynamics of fisher mobility for over larger spatial scales. The model can be used for investigating the complex interplay that exists between mobility and fish stock heterogeneity across regions, and the associated outcomes of mobility at the system level.

The model design informed by the example of small-scale fisheries in the Gulf of California, Mexico but implements theoretical and stylized facts and can as such be used for different archetypical cases. Our methodological approach for designing the model aims to account for the complex causation, emergence and interdependencies in small-scale fisheries to explain the phenomenon of sequential overexploitation, i.e., overexploiting one resource after another. The model is intended to be used as a virtual laboratory to investigate when and how different levels of mobile fishers affect exploitation patterns of fisheries resources.

PSoup is an educational program in which evolution is demonstrated, on the desk-top, as you watch. Blind bugs evolve sophisticated heuristic search algorithms to be the best at finding food fast.

The purpose of this model is to explain the post-disaster recovery of households residing in their own single-family homes and to predict households’ recovery decisions from drivers of recovery. Herein, a household’s recovery decision is repair/reconstruction of its damaged house to the pre-disaster condition, waiting without repair/reconstruction, or selling the house (and relocating). Recovery drivers include financial conditions and functionality of the community that is most important to a household. Financial conditions are evaluated by two categories of variables: costs and resources. Costs include repair/reconstruction costs and rent of another property when the primary house is uninhabitable. Resources comprise the money required to cover the costs of repair/reconstruction and to pay the rent (if required). The repair/reconstruction resources include settlement from the National Flood Insurance (NFI), Housing Assistance provided by the Federal Emergency Management Agency (FEMA-HA), disaster loan offered by the Small Business Administration (SBA loan), a share of household liquid assets, and Community Development Block Grant Disaster Recovery (CDBG-DR) fund provided by the Department of Housing and Urban Development (HUD). Further, household income determines the amount of rent that it can afford. Community conditions are assessed for each household based on the restoration of specific anchors. ASNA indexes (Nejat, Moradi, & Ghosh 2019) are used to identify the category of community anchors that is important to a recovery decision of each household. Accordingly, households are indexed into three classes for each of which recovery of infrastructure, neighbors, or community assets matters most. Further, among similar anchors, those anchors are important to a household that are located in its perceived neighborhood area (Moradi, Nejat, Hu, & Ghosh 2020).

The purpose of this agent-based model is to compare different variants of crowdworking in a general way, so that the obtained results are independent of specific details of the crowdworking platform. It features many adjustable parameters that can be used to calibrate the model to empirical data, but also when not calibrated it yields essential results about crowdworking in general.
Agents compete for contracts on a virtual crowdworking platform. Each agent is defined by various properties like qualification and income expectation. Agents that are unable to turn a profit have a chance to quit the crowdworking platform and new crowdworkers can replace them. Thus the model has features of an evolutionary process, filtering out the ill suited agents, and generating a realistic distribution of agents from an initially random one. To simulate a stable system, the amount of contracts issued per day can be set constant, as well as the number of crowdworkers. If one is interested in a dynamically changing platform, the simulation can also be initialized in a way that increases or decreases the number of crowdworkers or number of contracts over time. Thus, a large variety of scenarios can be investigated.

The intention of this model is to create an universal basis on how to model change in value prioritizations within social simulation. This model illustrates the designing of heterogeneous populations within agent-based social simulations by equipping agents with Dynamic Value-based Cognitive Architectures (DVCA-model). The DVCA-model uses the psychological theories on values by Schwartz (2012) and character traits by McCrae and Costa (2008) to create an unique trait- and value prioritization system for each individual. Furthermore, the DVCA-model simulates the impact of both social persuasion and life-events (e.g. information, experience) on the value systems of individuals by introducing the innovative concept of perception thermometers. Perception thermometers, controlled by the character traits, operate as buffers between the internal value prioritizations of agents and their external interactions. By introducing the concept of perception thermometers, the DVCA-model allows to study the dynamics of individual value prioritizations under a variety of internal and external perturbations over extensive time periods. Possible applications are the use of the DVCA-model within artificial sociality, opinion dynamics, social learning modelling, behavior selection algorithms and social-economic modelling.