A replication in Netlogo 5.2 of the classic model, Sugarscape (Epstein & Axtell, 1996).

UPDATE in V1.1.0: missing input data files added; relative paths to input data files changed to “../data/FILENAME”

A model that allows for representing key theories of Roman amphora reuse, to explore the differences in the distribution of amphorae, re-used amphorae and their contents.

This model generates simulated distributions of prime-use amphorae, primeuse contents (e.g. olive oil) and reused amphorae. These simulated distributions will differ between experiments depending on the experiment’s variable settings representing the tested theory: variations in the probability of reuse, the supply volume, the probability of reuse at ports. What we are interested in teasing out is what the effect is of each theory on the simulated amphora distributions.

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An agent model is presented that aims to capture the impact of cheap talk on collective action in a commons dilemma. The commons dilemma is represented as a spatially explicit renewable resource. Agent’s trust in others impacts the speed and harvesting rate, and trust is impacted by observed harvesting behavior and cheap talk. We calibrated the model using experimental data (DeCaro et al. 2021). The best fit to the data consists of a population with a small frequency of altruistic and selfish agents, and mostly conditional cooperative agents sensitive to inequality and cheap talk. This calibrated model provides an empirical test of the behavioral theory of collective action of Elinor Ostrom and Humanistic Rational Choice Theory.

Cultural group selection model used to evaluate the conditions for agents to evolve who have other-regarding preferences in making decisions in public good games.

The teamCognition model investigates team decision processes by using an agent-based model to conceptualize team decisions as an emergent property. It uses a mixed-method research design with a laboratory experiment providing qualitative and quantitative input for the model’s construction, as well as data for an output validation of the model. The agent-based model is used as a computational testbed to contrast several processes of team decision making, representing potential, simplified mechanisms of how a team decision emerges. The increasing overall fit of the simulation and empirical results indicates that the modeled decision processes can at least partly explain the observed team decisions.

Here we share the raw results of the social experiments of the paper “Gossip and competitive altruism support cooperation in a Public Good Game” by Giardini, Vilone, Sánchez, Antonioni, under review for Philosophical Transactions B. The experiment is thoroughly described there, in the following we summarize the main features of the experimental setup. The authors are available for further clarifications if requested.

Participants were recruited from the LINEEX subjects pool (University of Valencia Experimental Economics lab). 160 participants mean age = 21.7 years; 89 female) took part in this study in return for a flat payment of 5 EUR and the opportunity to earn an additional payment ranging from 8 to 16 EUR (mean total payment = 17.5 EUR). 80 subjects, divided into 5 groups of 16, took part in the competitive treatment while other 80 subjects participated in the non-competitive treatment. Laboratory experiments were conducted at LINEEX on September 16th and 17th, 2015.

The simulation is a variant of the “ToRealSim OD variants - base v2.7” base model, which is based on the standard DW opinion dynamics model (but with the differences that rather than one agent per tick randomly influencing another, all agents randomly influence one other per tick - this seems to make no difference to the outcomes other than to scale simulation time). Influence can be made one-way by turning off the two-way? switch

Various additional variations and sources of noise are possible to test robustness of outcomes to these (compared to DW model).
In this version agent opinions change following the empirical data collected in some experiments (Takács et al 2016).

Such an algorithm leaves no role for the uncertainties in other OD models. [Indeed the data from (Takács et al 2016) indicates that there can be influence even when opinion differences are large - which violates a core assumption of these]. However to allow better comparison with other such models there is a with-un? switch which allows uncertainties to come into play. If this is on, then influence (according to above algorithm) is only calculated if the opinion difference is less than the uncertainty. If an agent is influenced uncertainties are modified in the same way as standard DW models.

This repository includes an epidemic agent-based model that simulates the spread of Covid-19 epidemic. Normal.nlogo is the main file, while Exploring-zoning.nlogo and Exploring-Testing-With-Tracking.nlogo are modefied models to test the two strategies and run experiments.

Violence against women occurs predominantly in the family and domestic context. The COVID-19 pandemic led Brazil to recommend and, at times, impose social distancing, with the partial closure of economic activities, schools, and restrictions on events and public services. Preliminary evidence shows that intense co- existence increases domestic violence, while social distancing measures may have prevented access to public services and networks, information, and help. We propose an agent-based model (ABM), called VIDA, to illustrate and examine multi-causal factors that influence events that generate violence. A central part of the model is the multi-causal stress indicator, created as a probability trigger of domestic violence occurring within the family environment. Two experimental design tests were performed: (a) absence or presence of the deterrence system of domestic violence against women and measures to increase social distancing. VIDA presents comparative results for metropolitan regions and neighbourhoods considered in the experiments. Results suggest that social distancing measures, particularly those encouraging staying at home, may have increased domestic violence against women by about 10%. VIDA suggests further that more populated areas have comparatively fewer cases per hundred thousand women than less populous capitals or rural areas of urban concentrations. This paper contributes to the literature by formalising, to the best of our knowledge, the first model of domestic violence through agent-based modelling, using empirical detailed socioeconomic, demographic, educational, gender, and race data at the intraurban level (census sectors).

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.