Organizations are complex systems comprised of many dynamic and evolving interaction patterns among individuals and groups. Understanding these interactions and how patterns, such as informal structures and knowledge sharing behavior, emerge are crucial to creating effective and efficient organizations. To explore such organizational dynamics, the agent-based model integrates a cognitive model, dynamic social networks, and a physical environment.

NetCommons simulates a social dilemma process in case of step-level public goods. Is possible to generate (or load from DL format) any different networks, to change initial parameters, to replicate a number of experimental situations, and to obtain a event history database in CSV format with information about the context of each agents’ decision, the individual behavior and the aggregate outcomes.

Knowledge Based Economy (KBE) is an artificial economy where firms placed in geographical space develop original knowledge, imitate one another and eventually recombine pieces of knowledge. In KBE, consumer value arises from the capability of certain pieces of knowledge to bridge between existing items (e.g., Steve Jobs illustrated the first smartphone explaining that you could make a call with it, but also listen to music and navigate the Internet). Since KBE includes a mechanism for the generation of value, it works without utility functions and does not need to model market exchanges.

This model can be used to explore under which conditions agents behave as observed in field experiments on irrigation games.

The model simulates tail biting behaviour in pigs and how they can turn into a biter and/or victim. The effect of a redirected motivation, behavioural changes in victims and preference to bite a lying pig on tail biting can be tested in the model

The SMASH model is an agent-based model of rural smallholder households. It models households’ evolving income and wealth, which they earn through crop sales. Wealth is carried in the form of livestock, which are grazed on an external rangeland (exogenous) and can be bought/sold as investment/coping mechanisms. The model includes a stylized representation of soil nutrient dynamics, modeling the inflows and outflows of organic and inorganic nitrogen from each household’s field.

The model has been applied to assess the resilience-enhancing effects of two different farm-level adaptation strategies: legume cover cropping and crop insurance. These two strategies interact with the model through different mechanims - legume cover cropping through ecological mechanisms and crop insurance through financial mechanisms. The model can be used to investigate the short- and long-term effects of these strategies, as well as how they may differently benefit different types of household.

MOOvPOPsurveillance was developed as a tool for wildlife agencies to guide collection and analysis of disease surveillance data that relies on non-probabilistic methods like harvest-based sampling.

Routes & Rumours is an agent-based model of (forced) human migration. We model the formation of migration routes under the assumption that migrants have limited geographical knowledge concerning the transit area and rely to a large degree on information obtained from other migrants.

Model of shifting cultivation. All parameters can be controlled by the user or the model can be run in adaptive mode, in which agents innovate and select parameters.

The MOBILITY model analyzes how agents’ mobility affects the performance of social-ecological systems in different landscape configurations.