MoPAgrIB model simulates the movement of cultivated patches in a savannah vegetation mosaic ; how they move and relocate through the landscape, depending on farming practices, population growth, social rules and vegetation growth.

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.

We developed an agent-based model to explore underlying mechanisms of behavioral clustering that we observed in human online shopping experiments.

We model the relationship between natural resource user´s individual time preferences and their use of destructive extraction method in the context of small-scale fisheries.

Cultural group selection model used to evaluate the conditions for agents to evolve who have other-regarding preferences in making decisions in public good games.

A model to investigate the Evolution of Conditional Cooperation in a Spatial Public Goods Game. We consider two conditional cooperation strategies: one based on thresholds (Battu & Srinivasan, 2020) and another based on independent decisions for each number of cooperating neighbors. We examine the effects of productivity and conditional cooperation criteria on the trajectory of cooperation. Cooperation is evolving with no need for additional mechanisms apart from spatial structure when agents follow conditional strategies. We confirm the positive influence of productivity and cluster formation on the evolution of cooperation in spatial models. Results are robust for the two types of conditional cooperation strategies.

The purpose of this model is to investigate the consequences of helminthes in public health policy to eradicate tuberculosis. Helminthes surprise immune system responses and without changes in hygiene

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.

HUMLAND Fire-in-the-Hole is a conceptual agent-based model (ABM) designed to explore the ecological and behavioral consequences of fire-driven hunting strategies employed by hunter-gatherers, specifically Neanderthals, during the Last Interglacial period around the Neumark-Nord (Germany) archaeological site.

This model builds on and specializes the HUMLAND 1.0.0 model (Nikulina et al. 2024), integrating anthropogenic fires, elephant group behavior, and landscape response to simulate interactions between humans, megafauna, and vegetation over time.

The model objective’s is to explore the management choice set to uncover which subsets of strategies are most effective at maximizing species coexistence on a fragmented landscape.