This work is a java implementation of a study of the viability of a population submitted to floods. The population derives some benefit from living in a certain environment. However, in this environment, floods can occur and cause damage. An individual protection measure can be adopted by those who wish and have the means to do so. The protection measure reduces the damage in case of a flood. However, the effectiveness of this measure deteriorates over time. Individual motivation to adopt this measure is boosted by the occurrence of a flood. Moreover, the public authorities can encourage the population to adopt this measure by carrying out information campaigns, but this comes at a cost. People’s decisions are modelled based on the Protection Motivation Theory (Rogers1975, Rogers 1997, Maddux1983) arguing that the motivation to protect themselves depends on their perception of risk, their capacity to cope with risk and their socio-demographic characteristics.
While the control designing proper informations campaigns to remain viable every time is computed in the work presented in https://www.comses.net/codebases/e5c17b1f-0121-4461-9ae2-919b6fe27cc4/releases/1.0.0/, the aim of the present work is to produce maps of probable viability in case the serie of upcoming floods is unknown as well as much of the parameters for the population dynamics. These maps are bi-dimensional, based on the value of known parameters: the current average wealth of the population and their actual or possible future annual revenues.

The purpose of the model is to investigate how different factors affect the ability of researchers to reconstruct prehistoric social networks from artifact stylistic similarities, as well as the overall diversity of cultural traits observed in archaeological assemblages. Given that cultural transmission and evolution is affected by multiple interacting phenomena, our model allows to simultaneously explore six sets of factors that may condition how social networks relate to shared culture between individuals and groups:

1. Factors relating to the structure of social groups
2. Factors relating to the cultural traits in question
3. Factors relating to individual learning strategies
4. Factors relating to the environment
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This repository contains: (1) a model calibration procedure that identifies a set of diverse, plausible models; and (2) an ABM of smallholder agriculture, which is used as a case study application for the calibration method. By identifying a set of diverse models, the calibration method attends to the issue of “equifinality” prevalent in complex systems, which is a situation where multiple plausible process descriptions exist for a single outcome.

We present a socio-epistemic model of science inspired by the existing literature on opinion dynamics. In this model, we embed the agents (or scientists) into social networks - e.g., we link those who work in the same institutions. And we place them into a regular lattice - each representing a unique mental model. Thus, the global environment describes networks of concepts connected based on their similarity. For instance, we may interpret the neighbor lattices as two equivalent models, except one does not include a causal path between two variables.

Agents interact with one another and move across the epistemic lattices. In other words, we allow the agents to explore or travel across the mental models. However, we constrain their movements based on absorptive capacity and cognitive coherence. Namely, in each round, an agent picks a focal point - e.g., one of their colleagues - and will move towards it. But the agents’ ability to move and speed depends on how far apart they are from the focal point - and if their new position is cognitive/logic consistent.

Therefore, we propose an analytical model that examines the connection between agents’ accumulated knowledge, social learning, and the span of attitudes towards mental models in an artificial society. While we rely on the example from the General Theory of Relativity renaissance, our goal is to observe what determines the creation and diffusion of mental models. We offer quantitative and inductive research, which collects data from an artificial environment to elaborate generalized theories about the evolution of science.

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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Schelling and Sakoda prominently proposed computational models suggesting that strong ethnic residential segregation can be the unintended outcome of a self-reinforcing dynamic driven by choices of individuals with rather tolerant ethnic preferences. There are only few attempts to apply this view to school choice, another important arena in which ethnic segregation occurs. In the current paper, we explore with an agent-based theoretical model similar to those proposed for residential segregation, how ethnic tolerance among parents can affect the level of school segregation. More specifically, we ask whether and under which conditions school segregation could be reduced if more parents hold tolerant ethnic preferences. We move beyond earlier models of school segregation in three ways. First, we model individual school choices using a random utility discrete choice approach. Second, we vary the pattern of ethnic segregation in the residential context of school choices systematically, comparing residential maps in which segregation is unrelated to parents’ level of tolerance to residential maps reflecting their ethnic preferences. Third, we introduce heterogeneity in tolerance levels among parents belonging to the same group. Our simulation experiments suggest that ethnic school segregation can be a very robust phenomenon, occurring even when about half of the population prefers mixed to segregated schools. However, we also identify a “sweet spot” in the parameter space in which a larger proportion of tolerant parents makes the biggest difference. This is the case when parents have moderate preferences for nearby schools and there is only little residential segregation. Further experiments are presented that unravel the underlying mechanisms.

We develop a spatial, evolutionary model of the endogenous formation and dissolution of groups using a renewable common pool resource. We use this foundation to measure the evolutionary pressures at different organizational levels.

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).

This Repast Simphony model simulates genomic admixture during the farming expansion of human groups from mainland Asia into the Papuan dominated islands of Southeast Asia during the Neolithic period.

We expose RA agent-based model of the opinion and tolerance dynamics in artificial societies. The formal mathematical model is based on the ideas of Social Influence, Social Judgment, and Social Identity theories.