The Pampas Model is an Agent-Based Model intended to explore the dynamics of structural and land use changes in agricultural systems of the Argentine Pampas in response to climatic, technological economic, and political drivers.

This multi-model (i.e. a model composed of interacting submodels) is a multi-level representation of a collective motion phenomenon. It was designed to study the impact of the mutual influences between individuals and groups in collective motion.

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.

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).

To investigate the potential of using Social Psychology Theory in ABMs of natural resource use and show proof of concept, we present an exemplary agent-based modelling framework that explicitly represents multiple and hierarchical agent self-concepts

This simulation model is to simulate the emergence of technological innovation processes from the hypercycles perspective.

The various technologies used inside a Dutch greenhouse interact in combination with an external climate, resulting in an emergent internal climate, which contributes to the final productivity of the greenhouse. This model examines how differing technology development styles affects the overall ability of a community of growers to approach the theoretical maximum yield.

This Agent-Based model intends to explore the conditions for the emergence and change of land use patterns in Central Asian oases and similar contexts.

Simulates impacts of ants killing colony mates when in conflict with another nest. The murder rate is adjustable, and the environmental change is variable. The colonies employ social learning so knowledge diffusion proceeds if interactions occur.