The model answers the question how homophily and number of close-links in small-world network influences behavior of consumats. The results show that the more close-links the more probable the consumat follows the major behavior, but homophilly blocks the major behavior and supports survival of the minor behavior.

The model explores the impact of journal metrics (e.g., the notorious impact factor) on the perception that academics have of an article’s scientific value.

This models simulates innovation diffusion curves and it tests the effects of the degree and the direction of social influences. This model replicates, extends and departs from classical percolation models.

A logging agent builds roads based on the location of high-value hotspots, and cuts trees based on road access. A forest monitor sanctions the logger on observed infractions, reshaping the pattern of road development.

We extend the Flache-Mäs model to incorporate the location and dyadic communication regime of the agents in the opinion formation process. We make spatially proximate agents more likely to interact with each other in a pairwise communication regime.

We build a computational model to investigate, in an evolutionary setting, a series of questions pertaining to happiness.

EffLab was built to support the study of the efficiency of agents in an evolving complex adaptive system. In particular:
- There is a definition of efficiency used in ecology, and an analogous definition widely used in business. In ecological studies it is called EROEI (energy returned on energy invested), or, more briefly, EROI (pronounced E-Roy). In business it is called ROI (dollars returned on dollars invested).
- In addition, there is the more well-known definition of efficiency first described by Sadi Carnot, and widely used by engineers. It is usually represented by the Greek letter ‘h’ (pronounced as ETA). These two measures of efficiency bear a peculiar relationship to each other: EROI = 1 / ( 1 - ETA )

In EffLab, blind seekers wander through a forest looking for energy-rich food. In this multi-generational world, they live and reproduce, or die, depending on whether they can find food more effectively than their contemporaries. Data is collected to measure their efficiency as they evolve more effective search patterns.

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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.

The WaterScape is an agent-based model of the South African water sector. This version of the model focuses on potential barriers to learning in water management that arise from interactions between human perceptions and social-ecological system conditions.

Continuing on from the Adder model, this adaptation explores how rationality, learning and uncertainty influence the exploration of complex landscapes representing technological evolution.