The aim of this model is to explore and understand the factors driving adoption of treatment strategies for ecological disturbances, considering payoff signals, learning strategies and social-ecological network structure

This model makes it possible to explore how network clustering and resistance to changing existing status beliefs might affect the spontaneous emergence and diffusion of such beliefs as described by status construction theory.

The model studies the dynamics of risk-sharing cooperatives among heterogeneous farmers. Based on their knowledge on their risk exposure and the performance of the cooperative farmers choose whether or not to remain in the risk-sharing agreement.

The ana-wag model, for Analyse Wat-A-Game (WAG), is a NetLogo version of the WAG role playing game. It enables to model a river catchment with the graphical modelling language WAG and to play it as a network-game (each player is a water user).

This Repast Simphony model simulates genomic admixture during the farming expansion of human groups from mainland Asia into the Papuan dominated islands of Southeast Asia during the Neolithic period.

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.

The model provides instruments for the simulation of interbank network evolution. There are tools for dynamic network analysis, allowing to evaluate graph topological invariants, thermodynamic network features and combinational node-based features.

The model’s purpose is to provide a potential explanation for the emergence, sustenance and decline of unpopular norms based on pluralistic ignorance on a social network.

This Bicycle encounter model builds on the Salzburg Bicycle model (Wallentin & Loidl, 2015). It simulates cyclist flows and encounters, which are locations of potential accidents between cyclists.

An ABM to simulate the spatio-temporal distribution of cyclists across the road network of the city of Salzburg.