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.

The model aims to illustrate how Earned Value Management (EVM) provides an approach to measure a project’s performance by comparing its actual progress against the planned one, allowing it to evaluate trends to formulate forecasts. The instance performs a project execution and calculates the EVM performance indexes according to a Performance Measurement Baseline (PMB), which integrates the description of the work to do (scope), the deadlines for its execution (schedule), and the calculation of its costs and the resources required for its implementation (cost).

Specifically, we are addressing the following questions: How does the risk of execution delay or advance impact cost and schedule performance? How do the players’ number or individual work capacity impact cost and schedule estimations to finish? Regardless of why workers cause delays or produce overruns in their assignments, does EVM assess delivery performance and help make objective decisions?

To consider our model realistic enough for its purpose, we use the following patterns: The model addresses classic problems of Project Management (PM). It plays the typical task board where workers are assigned to complete a task backlog in project performance. Workers could delay or advance in the task execution, and we calculate the performance using the PMI-recommended Earned Value.

We construct an agent-based model to investigate and understand the roles of green attachment, engagement in local ecological investment (i.e., greening), and social feedback.

The model reproduces the spread of environmental awareness among agents and the impact of awareness level of the agents on the consumption of a resource, like energy. An agent is a household with a set of available advanced smart metering functions.

The model explores the impact of public disclosure on tax compliance among diverse agents, including individual taxpayers and a tax authority. It incorporates heterogeneous preferences and income endowments among taxpayers, captured through a utility function that considers psychic costs subtracted from expected pecuniary utility. These costs include moral, reciprocity, and stigma costs associated with norm violations, leading to variations in taxpayers’ risk attitudes and related parameters. The tax authority’s attributes, such as the frequency of random audits, penalty rate, and the choice between partial or full disclosure, remain fixed throughout the simulation. Income endowments and preference parameters are randomly assigned to taxpayers at the outset.

Taxpayers maximize their expected utility by reporting income, taking into account tax, penalty, and audit rates. They make annual decisions based on their own and their peers’ behaviors from the previous year. Taxpayers indirectly interact at the societal level through public disclosure conducted by the tax authority, exchanging tax information among peers. Each period in the simulation collects data on total reported income, average compliance rates per income group, distribution of compliance rates, counts of compliers, full evaders, partial evaders, and the numbers of taxpayers experiencing guilt and anger. The model evaluates whether public disclosure positively or negatively impacts compliance rates and quantifies this impact based on aggregated individual reporting behaviors.

An ABM, derived from a case study and a series of surveys with greenhouse growers in the Westland, Netherlands. Experiments using this model showshow that the greenhouse horticulture industry displays diversity, adaptive complexity and an uneven distribution, which all suggest that the industry is an evolving system.

We seek to improve understanding of roles enzyme play in soil food webs. We created an agent-based simulation of a simple food web that includes enzymatic activity. The model was used in a publication, Moore et al. (in press; Biochemistry).

The Hohokam Trade Networks Model focuses on key features of the Hohokam economy to explore how differences in trade network topologies may show up in the archaeological record. The model is set in the Phoenix Basin of central Arizona, AD 200-1450.

The FishCensus model simulates underwater visual census methods, where a diver estimates the abundance of fish. A separate model is used to shape species behaviours and save them to a file that can be shared and used by the counting model.

The purpose of this model is to explore the effects of different power structures on a cross-functional team’s prosocial decision making. Are certain power distributions more conducive to the team making prosocial decisions?