In 1985 Dr Michael Palmiter, a high school teacher, first built a very innovative agent-based model called “Simulated Evolution” which he used for teaching the dynamics of evolution. In his model, students can see the visual effects of evolution as it proceeds right in front of their eyes. Using his schema, small linear changes in the agent’s genotype have an exponential effect on the agent’s phenotype. Natural selection therefore happens quickly and effectively. I have used his approach to managing the evolution of competing agents in a variety of models that I have used to study the fundamental dynamics of sustainable economic systems. For example, here is a brief list of some of my models that use “Palmiter Genes”:
- ModEco - Palmiter genes are used to encode negotiation strategies for setting prices;
- PSoup - Palmiter genes are used to control both motion and metabolic evolution;
- TpLab - Palmiter genes are used to study the evolution of belief systems;
- EffLab - Palmiter genes are used to study Jevon’s Paradox, EROI and other things.

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How can a strictly egalitarian social system give way to a stratified society if all of its members punish each other for any type of selfish behavior? This model examines the role of prestige bias in constant and variable environments on the development of hierarchies of wealth.

More frequently protests are accompanied by an opposing group performing a counter protest. This phenomenon can increase tension such that police must try to keep the two groups separated. However, what is the best strategy for police? This paper uses a simple agent-based model to determine the best strategy for keeping the two groups separated. The ‘thin blue line’ varies in density (number of police), width and the keenness of police to approach protesters. Three different groups of protesters are modelled to mimic peaceful, average and volatile protests. In most cases, a few police forming a single-file ‘thin blue line’ separating the groups is very effective. However, when the protests are more volatile, it is more effective to have many police occupying a wide ‘thin blue line’, and police being keen to approach protesters. To the authors knowledge, this is the first paper to model protests and counter-protests.

This agent-based model investigates group longevity in a population in a foundational way, using theory on social relations and culture. It is the first application of the GRASP meta-model for social agents, containing elements of Groups, Rituals, Affiliation, Status, and Power. It can be considered an exercise in artificial sociality: a culture-general, content-free base-line trust model from which to engage in more specific studies. Depending on cultural settings for individualism and power distance, as well as settings for xenophobia and for the increase of trust over group life, the GRASP world model generates a variety of patters. Number of groups ranges from one to many, composition from random to segregated, and pattern genesis from rapid to many hundreds of time steps. This makes GRASP world an instrument that plausibly models some basic elements of social structure in different societies.

The purpose of the model is to explore the influence of the design of circular business models (CBMs) on CBM viability. The model represents an Industrial Symbiosis Network (ISN) in which a processor uses the organic waste from suppliers to produce biogas and nutrient rich digestate for local reuse. CBM viability is expressed as value captured (e.g., cash flow/tonne waste/agent) and the survival of the network over time (shown in the interface).

In the model, the value captured is calculated relative to the initial state, using incineration costs as a benchmark. Moderating variables are interactions with the waste incinerator and actor behaviour factors. Actors may leave the network when the waste supply for local production is too low, or when personal economic benefits are too low. When the processor decides to leave, the network fails. Theory of planned behaviour can be used to include agent behaviour in the simulations.

ICARUS is a multi-agent compliance inspection model (ICARUS - Inspecting Compliance to mAny RUleS). The model is applicable to environments where an inspection agency, via centrally coordinated inspections, examines compliance in organizations which must comply with multiple provisions (rules). The model (ICARUS) contains 3 types of agents: entities, inspection agency and inspectors / inspections. ICARUS describes a repeated, simultaneous, non-cooperative game of pure competition. Agents have imperfect, incomplete, asymmetric information. Entities in each move (tick) choose a pure strategy (comply/violate) for each rule, depending on their own subjective assessment of the probability of the inspection. The Inspection Agency carries out the given inspection strategy.

A more detailed description of the model is available in the .nlogo file.
Full description of the model (in line with the ODD+D protocol) and the analysis of the model (including verification, validation and sensitivity analysis) can be found in the attached documentation.

This package implements a simplified artificial agent-based demographic model of the UK. Individuals of an initial population are subject to ageing, deaths, births, divorces and marriages. A specific case-study simulation is progressed with a user-defined simulation fixed step size on a hourly, daily, weekly, monthly basis or even an arbitrary user-defined clock rate. While the model can serve as a base model to be adjusted to realistic large-scale socio-economics, pandemics or social interactions-based studies mainly within a demographic context, the main purpose of the model is to explore and exploit capabilities of the state-of-the-art Agents.jl Julia package as well as other ecosystem of Julia packages like GlobalSensitivity.jl. Code includes examples for evaluating global sensitivity analysis using Morris and Sobol methods and local sensitivity analysis using OFAT and OAT methods. Multi-threaded parallelization is enabled for improved runtime performance.

This generic individual-based model of a bird colony shows how the influence neighbour’s stress levels synchronize the laying date of neighbours and also of large colonies. The model has been used to demonstrate how this form of simulation model can be recognised as being ‘event-driven’, retaining a history in the patterns produced via simulated events and interactions.

Purpose of the model is to perform a “virtual experiment” to test the predator satiation hypothesis, advanced in literature to explain the mast seeding phenomenon.

A global model of the 1918-19 Influenza Pandemic. It can be run to match history or explore counterfactual questions about the influence of World War I on the dynamics of the epidemic. Explores two theories of the location of the initial infection.