The purpose of this model is to explore the dynamics of residency and eviction for households renting in the greater Phoenix (Arizona) metropolitan area. The model uses a representative population of renters modified from American Community Survey (ACS) data that includes demographic, housing and economic information. Each month, households pay their subsistence, rental and utility bills. If a household is unable to pay their monthly rent or utility bill they apply for financial assistance. This model provides a platform to understand the impact of various economic shock upon households. Also, the model includes conditions that occurred as a result of the Covid-19 pandemic which allows for the study of eviction mitigation strategies that were employed, such as the eviction moratorium and stimulus payments. The model allows us to make preliminary predictions concerning the number of households that may be evicted once the moratorium on evictions ends and the long-term effects on the number of evicted households in the greater Phoenix area going forward.

This ABM simulates problem solving agents as they work on a set of tasks. Each agent has a trait vector describing their skills. Two agents might form a collaboration if their traits are similar enough. Tasks are defined by a component vector. Agents work on tasks by decreasing tasks’ component vectors towards zero.

The simulation generates agents with given intrapersonal functional diversity (IFD), and dominant function diversity (DFD), and a set of random tasks and evaluates how agents’ traits influence their level of communication and the performance of a team of agents.

Modeling results highlight the importance of the distributions of agents’ properties forming a team, and suggests that for a thorough description of management teams, not only diversity measures based on individual agents, but an aggregate measure is also required.

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Flibs’NLogo implements in NetLogo modelling environment, a genetic algorithm whose purpose is evolving a perfect predictor from a pool of digital creatures constituted by finite automata or flibs (finite living blobs) that are the agents of the model. The project is based on the structure described by Alexander K. Dewdney in “Exploring the field of genetic algorithms in a primordial computer sea full of flibs” from the vintage Scientific American column “Computer Recreations”.
As Dewdney summarized: “Flibs […] attempt to predict changes in their environment. In the primordial computer soup, during each generation, the best predictor crosses chromosomes with a randomly selected flib. Increasingly accurate predictors evolve until a perfect one emerges. A flib […] has a finite number of states, and for each signal it receives (a 0 or a 1) it sends a signal and enters a new state. The signal sent by a flib during each cycle of operation is its prediction of the next signal to be received from the environment”

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.

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This is model that simulates how multiple kinds of peer effects shape the diffusion of innovations through different types of social relationships.

We model interpersonal dynamics and study behavior in the classroom in the hypothetical case of a single teacher who defines students’ seating arrangements. The model incorporates the mechanisms of peer influence on study behavior, on attitude formation, and homophilous selection in order to depict the interrelated dynamics of networks, behavior, and attitudes. We compare various seating arrangement scenarios and observe how GPA distribution and level of prejudice changes over time.

The purpose of this agent-based model is to explore the emergent phenomena associated with scientific publication, including quantity and quality, from different academic types based on their publication strategies.

Brazil has initiated two territorial public policies for a rural sustainable development, the National Program for Sustainable Development of the Rural Territories (PRONAT) and Citizenship Territory Program (PTC). These public policies aims, as a condition for its effectiveness, the equilibrium of the power relations between actors which participate in the Collegiate for Territorial Development (CODETER) of each Rural Territory. Our research studies the hypotheses that, in the Rural Territories submitted to the PRONAT and PTC public policies, the power and reciprocity relations between actors engaged in the CODETER effectively have evolved in favor of the civil society representatives to the detriment of the public powers, notably the mayors.

The SocLab approach has been applied in two case studies and four models representing the Southern Rural Territory of Sergipe (TRSS) and the São Francisco Rural Territory (TRBSF) were designed for two referential periods, 2008-2012 and 2013-2017. These models were developed to evaluate the empowerment of the civil society in these rural territories due to thes two public policies, PRONAT and PTC.

Car-centric societies face substantial challenges in moving towards sustainable
mobility systems, with internal combustion engine vehicles remaining a major
source of emissions. Electric vehicles play a critical role in addressing this challenge, yet their diffusion depends on the interaction of consumer behaviour, firm
innovation, and policy incentives. This paper develops an agent-based model to
examine these dynamics, calibrated on the data for the state of California over
2001-2023. In the model, heterogeneous car users influenced by their social peers
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The basic idea behind developing MIXTRUST was to represent a network of agricultural stakeholders composed of farmers and a cooperative in a mixed landscape to test its performances in response to risks. A mixed landscape here is a landscape where crop and livestock systems interact by the intermediary of material flows of agricultural products. It can be within mixed farms, or between farms, often specialized, (e.g. straw-manure).