We used our model to test how different combinations of dominance interactions present in H. saltator could result in linear, despotic, or shared hierarchies.

This is model that simulates how multiple kinds of peer effects shape the diffusion of innovations through different types of social relationships.

We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.

This is an agent-based model of the implementation of the self-enforcing agreement in cooperative teams.

The model is an extension of: Carley K. (1991) “A theory of group stability”, American Sociological Review, vol. 56, pp. 331-354.

The original model from Carley (1991) works as follows:
- Agents know or ignore a series of knowledge facts;
- At each time step, each agent i choose a partner j to interact with at random, with a probability of choice proportional to the degree of knowledge facts they have in common.
- Agents interact synchronously. As such, interaction happens only if the partnert j is not already busy interacting with someone else.
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The model combines the two elements of disorganization and motivation to explore their impact on teams. Effects of disorganization on team task performance (problem solving)

The HUMan impact on LANDscapes (HUMLAND) model has been developed to track and quantify the intensity of different impacts on landscapes at the continental level. This agent-based model focuses on determining the most influential factors in the transformation of interglacial vegetation with a specific emphasis on burning organized by hunter-gatherers. HUMLAND integrates various spatial datasets as input and target for the agent-based model results. Additionally, the simulation incorporates recently obtained continental-scale estimations of fire return intervals and the speed of vegetation regrowth. The obtained results include maps of possible scenarios of modified landscapes in the past and quantification of the impact of each agent, including climate, humans, megafauna, and natural fires.

ACT is an ABM based on an existing conceptualisation of the concept of critical transitions applied to the energy transition. With the model we departed from the mean-field approach simulated relevant actor behaviour in the energy transition.

This repository contains the Python implementation of an agent-based model investigating how localized boundary-crossing dynamics generate large-scale connectivity in structured multi-attractor landscapes.

Agents evolve in a continuous two-dimensional environment composed of attractor basins. A fraction of agents exhibits exploratory higher-mobility dynamics, while the remaining agents remain locally constrained. The model analyzes how localized configurational transitions accumulate into transition networks that progressively integrate the explored state space.

The repository includes:

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A haystack-style model of group selection to capture the essential features of colony foundation for queens of the ant based on observation of the ant Pogonomyrmex californicus.