The set of models test how receivers ability to accurately rank signalers under various ecological and behavioral contexts.

RAGE models a stylized common property grazing system. Agents follow a certain behavioral type. The model allows analyzing how household behavior with respect to a social norm on pasture resting affects long-term social-ecological system dynamics.

Interest-based compound economies generate monotonically increasing wealth inequality through multiplicative accumulation dynamics, yet the conditions under which gift-based reciprocal exchange outperforms such systems in collective well-being remain unquantified. We present Zensei Wago (全生和合), a seven-layer agent-based model comparing a Gift Resource Circulation (GRC) economy with a Compound Interest Circulation (CIC) economy under identical initial conditions. Across N = 5000 Monte Carlo replications (T = 700 ticks, N = 100 agents), GRC produced significantly higher collective resonance than CIC (p < 0.001, Cohen’s d = +0.171), above a critical prosocial threshold pm ≈ 0.698. Cohen’s d grows monotonically with duration — d = +1.943 at T = 1500 and d = +4.126 at T = 3000 — driven primarily by structural collapse of CIC resonance as inequality exceeds a critical Gini threshold (G > 0.333), while GRC resonance remains stable. The gift mechanism further decouples collective well-being from distributional outcomes, generating resonance through relational quality rather than material redistribution. Network topology analysis across seven configurations — combining a Watts-Strogatz rewiring sweep and a T = 1500 longitudinal replication — reveals that ring topology maximises GRC advantage (d = +1.17), that most topology-dependent reversals are transient (sparse and small-world both transition to significantly positive by T = 1500), and that a critical rewiring threshold of p ≈ 0.10–0.20 separates GRC-advantaged from GRC-disadvantaged network configurations. Scale-free networks remain persistently adverse (d = -7.24*), requiring structural redesign for gift-economy viability.

The study goes back to a model created in the 1990s which successfully tried to replicate the changes of the percentages of female teachers among the teaching staff in high schools (“Gymnasien”) in the German federal state of Rheinland-Pfalz. The current version allows for additional validation and calibration of the model and is accompanied with the empirical data against which the model is tested and with an analysis program especially designed to perform the analyses in the most recent journal article.

This is an extended replication of Abelson’s and Bernstein’s early computer simulation model of community referendum controversies which was originally published in 1963 and often cited, but seldom analysed in detail. This replication is in NetLogo 6.3.0, accompanied with an ODD+D protocol and class and sequence diagrams.

This replication replaces the original scales for attitude position and interest in the referendum issue which were distributed between 0 and 1 with values that are initialised according to a normal distribution with mean 0 and variance 1 to make simulation results easier compatible with scales derived from empirical data collected in surveys such as the European Value Study which often are derived via factor analysis or principal component analysis from the answers to sets of questions.

Another difference is that this model is not only run for Abelson’s and Bernstein’s ten week referendum campaign but for an arbitrary time in order that one can find out whether the distributions of attitude position and interest in the (still one-dimensional) issue stabilise in the long run.

This paper tries to shed some light on the mutual influence of citizen behaviour and the spread of a virus in an epidemic. While the spread of a virus from infectious to susceptible persons and the outbreak of an infection leading to more or less severe illness and, finally, to recovery and immunity or death has been modelled with different kinds of models in the past, the influence of certain behaviours to keep the epidemic low and to follow recommendations of others to apply these behaviours has rarely been modelled. The model introduced here uses a theory of the effect of norm invocations among persons to find out the effect of spreading norms interacts with the progress of an epidemic. Results show that norm invocations matter. The model replicates the histories of the COVID-19 epidemic in various region, including “second waves” (but only until the end of 2021 as afterwards the official statistics ceased to be reliable as many infected persons did not report their positive test results after countermeasures were relieved), and shows that the calculation of the reproduction numbers from current reported infections usually overestimates the “real” but in practice unobservable reproduction number.

The purpose of this study is another agent-based replication of a System Dynamics model (Anderson,1973) where he analysed the dynamics of nutrient, biomass, oxygen and detritus in a model lake under conditions of artificial fertilising and policies to deal with the consequences of artificial fertilising.. A first replication (Möhring & Troitzsch,2001) added those agents to the original model that were necessary to move the role of the experimenter into the model, whereas this replication replaces the original lake with a collection of small elements between which biomass, nurtrents and oxygen are exchanged, adds rivers upstream and downstream as well as adjacent land divided into villages and populated with farms and industrial plants run by individual persons.

A flexible framework for Agent-Based Models (ABM), the ‘epiworldR’ package provides methods for prototyping disease outbreaks and transmission models using a ‘C++’ backend, making it very fast. It supports multiple epidemiological models, including the Susceptible-Infected-Susceptible (SIS), Susceptible-Infected-Removed (SIR), Susceptible-Exposed-Infected-Removed (SEIR), and others, involving arbitrary mitigation policies and multiple-disease models. Users can specify infectiousness/susceptibility rates as a function of agents’ features, providing great complexity for the model dynamics. Furthermore, ‘epiworldR’ is ideal for simulation studies featuring large populations.

MarPEM is an agent-based model that can be used to study the effects of policy instruments on the transition away from HFO.

This is a coupled conceptual model of agricultural land decision-making and incentivisation and species metacommunities.