Genetic algorithms try to solve a computational problem following some principles of organic evolution. This model has educational purposes; it can give us an answer to the simple arithmetic problem on how to find the highest natural number composed by a given number of digits. We approach the task using a genetic algorithm, where the candidate solutions to the problem are represented by agents, that in logo programming environment are usually known as “turtles”.

On July 20th, James Holmes committed a mass shooting in a midnight showing of The Dark Knight Rises. The Aurora Colorado shooting was used as a test case to validate this framework for modeling mass shootings.

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 code contains four experiments for well-being based IMRL reward features.

We consider scientific communities where each scientist employs one of two characteristic methods: an “adequate” method (A) and a “superior” method (S). The quality of methodology is relevant to the epistemic products of these scientists, and generate credit for their users. Higher-credit methods tend to be imitated, allowing to explore whether communities will adopt one method or the other. We use the model to examine the effects of (1) bias for existing methods, (2) competence to assess relative value of competing methods, and (3) two forms of interdisciplinarity: (a) the tendency for members of a scientific community to receive meaningful credit assignment from those outside their community, and (b) the tendency to consider new methods used outside their community. The model can be used to show how interdisciplinarity can overcome the effects of bias and incompetence for the spread of superior methods.

This model is pertinent to our JASSS publication “Raising the Spectrum of Polarization: Generating Issue Alignment with a Weighted Balance Opinion Dynamics Model”. It shows how, based on the mechanisms of our Weighted Balance Theory (a development of Fritz Heider’s Cognitive Balance Theory), agents can self-organize in a multi-dimensional opinion space and form an emergent ideological spectrum. The degree of issue alignment and polarization realized by the model depends mainly on the agent-specific ‘equanimity parameter’ epsilon.

The objective of this agent-based model is to test different language education orientations and their consequences for the EU population in terms of linguistic disenfranchisement, that is, the inability of citizens to understand EU documents and parliamentary discussions should their native language(s) no longer be official. I will focus on the impact of linguistic distance and language learning. Ideally, this model would be a tool to help EU policy makers make informed decisions about language practices and education policies, taking into account their consequences in terms of diversity and linguistic disenfranchisement. The model can be used to force agents to make certain choices in terms of language skills acquisition. The user can then go on to compare different scenarios in which language skills are acquired according to different rationales. The idea is that, by forcing agents to adopt certain language learning strategies, the model user can simulate policies promoting the acquisition of language skills and get an idea of their impact. In this way the model allows not only to sketch various scenarios of the evolution of language skills among EU citizens, but also to estimate the level of disenfranchisement in each of these scenarios.

Merger and acquisition (M&A) activity has many strategic and operational objectives. One operational objective is to develop common and efficient information systems that maybe the source of creating

FlowLogo integrates agent-based and groundwater flow simulation. It aims to simplify the process of developing participatory ABMs in the groundwater space and begin the exploration of novel, bottom-up solutions to conflicts in shared aquifers.

The model combines agent-based modelling and microeconomic approach to simulate the decision behaviour of land developers and how this impacts on the spatio-temporal processes of urban expansion.