Swidden Farming is designed to explore the dynamics of agricultural land management strategies.

This simulation model is associated with the journal paper “A First Approach on Modelling Staff Proactiveness in Retail Simulation Models” to appear in the Journal of Artificial Societies and Social Simulation 14 (2) 2. The authors are Peer-Olaf Siebers (pos@cs.nott.ac.uk) and Uwe Aickelin (uxa@cs.nott.ac.uk).

An Agent-based model simulates consumer demand for Smart Metering tariffs. It utilizes the Bass Diffusion Model and Rogers´s adopter categories. Integration of empirical census microdata enables a validated socio-economic background for each consumer.

An algorithm implemented in NetLogo that can be used for searching resources.

We provide a full description of the model following the ODD protocol (Grimm et al. 2010) in the attached document. The model is developed in NetLogo 5.0 (Wilenski 1999).

A simulated approach for Personal Carbon Trading, for figuring out what effects it might have if it will be implemented in the real world. We use an artificial population with some empirical data from international literature and basic assumptions about heterogeneous energy demand. The model is not to be used as simulating the actual behavior of real populations, but a toy model to test the effects of differences in various factors such as number of agents, energy price, price of allowances, etc. It is important to adapt the model for specific countries as carbon footprint and energy demand determines the relative success of PCT.

This model explores different aspects of the formation of urban neighbourhoods where residents believe in values distant from those dominant in society. Or, at least, this is what the Danish government beliefs when they discuss their politics about parallel societies. This simulation is set to understand (a) whether these alternative values areas form and what determines their formation, (b) if they are linked to low or no income residents, and (c) what happens if they disappear from the map. All these three points are part of the Danish government policy. This agent-based model is set to understand the boundaries and effects of this policy.

The application of a smartphone application to register physical encounters between individuals is considered by public health authorities, as a means to reduce the number of infections in the 2020 COVID-19 pandemic. The general idea is that continuous registration of all other smartphones in the vicinity of an individual’s smartphone potentially enables early warning of the owners of the other smartphones, in case the individual is tested positive as infected. Those other individuals can then go into isolation and be considered for testing. The purpose of the present simulation is to explore the potential effects of this application on frequencies of infection, isolation, and positive and negative infection test results.

Communication processes occur in complex dynamic systems impacted by person attitudes and beliefs, environmental affordances, interpersonal interactions and other variables that all change over time. Many of the current approaches utilized by Communication researchers are unable to consider the full complexity of communication systems or the over time nature of our data. We apply agent-based modeling to the Reinforcing Spirals Model and the Spiral of Silence to better elucidate the complex and dynamic nature of this process. Our preliminary results illustrate how environmental affordances (i.e. social media), closeness of the system and probability of outspokenness may impact how attitudes change over time. Additional analyses are also proposed.

GenoScope is a modular agent-based model designed to simulate how cells respond to environmental stressors or other treatment conditions across species. Genes, treatment conditions, and cell physiology outcomes are represented as interacting agents that influence each other’s behavior over time. Rather than imposing fixed interaction rules, GenoScope initializes with randomized regulatory logic and calibrates rule sets based on empirical data. Calibration is grounded in a common-garden experiment involving 16 mammalian species—including humans, dolphins, bats, and camels—exposed to varying levels of temperature, glucose, and oxygen. This comparative approach enables the identification of mechanisms by which animal cells achieve robustness under extreme environmental conditions.