A dynamic model of social network formation on single-layer and multiplex networks with structural incentives that vary over time.

The Mobility Model is a model of a small-scale fishery with the purpose to study the movement of fishers between different sub-regions within a larger region, as they move between different regions to fish.

Agers and non-agers agent compete over a spatial landscape. When two agents occupy the same grid, who will survive is decided by a random draw where chances of survival are proportional to fitness. Agents have offspring each time step who are born at a distance b from the parent agent and the offpring inherits their genetic fitness plus a random term. Genetic fitness decreases with time, representing environmental change but effective non-inheritable fitness can increase as animals learn and get bigger.

This software simulates cars and bicycles as traffic participants while crossing different crossroad designs such as roundabouts, protected crossroads and standard crossroads. It is written in Netlogo 6.2 and aims to identify safety characteristics of these layouts using agent-based modeling. Participants track the line of sight to each other and print them as an output alongside with the adjacent destination, used layout, count of collisions/cars/bicycles and time.

Detailed information can be found within the info tab of the program itself.

This model explores the coupled dynamics of social norm diffusion and finite resource depletion. Extending the “Affordance Landscape” framework by Kaaronen & Strelkovskii (2020), this simulation investigates how resource scarcity and regeneration rates influence the adoption of pro-environmental behaviours.

The model addresses the gap by linking behavioural norms to a depleting common-pool resource. It tests whether sustainable norms can diffuse rapidly enough to prevent ecological collapse and identifies “tipping points” where resource scarcity acts as a driver for behavioural change.

This model simulates a forest ecosystem affected by human logging. We explore different kind of approaches and their possible consequences for the ecosystem. Loggers can either be responsible or irresponsible, they will either take care to cut trees or not. In turn their actions will have consequences on the quality of the soil, the atmosphere as well as their profit made from logging. In this model we see that even careful management cannot prevent the degradation of the forest ecosystem.

DIAL is a model of group dynamics and opinion dynamics. It features dialogues, in which agents put their reputation at stake. Intra-group radicalisation of opinions appears to be an emergent phenomenon.

Dynamic bipartite network model of agents and games in which agents can participate in multiple public goods games.

REHAB has been designed as an ice-breaker in courses dealing with ecosystem management and participatory modelling. It helps introducing the two main tools used by the Companion Modelling approach, namely role-playing games and agent-based models.

Reusing existing material stocks in developed built environments can significantly reduce the environmental footprint of the construction and demolition sector. However, material reuse in urban areas presents technical, temporal, and geographical challenges. Although a better understanding of spatial and temporal changes in material stocks could improve city resource management, limited scientific contributions have addressed this challenge.
This study details the steps followed in developing a spatially explicit rule-based simulation of materials stock. The simulation provides a proof of concept by incorporating the spatial and temporal dimensions of construction and demolition activities to analyse how various urban parameters determine material flows and embodied carbon in urban areas. The model explores the effects of 1) re-using recycled materials, 2) demolitions, 3) renovations and 4) various building typologies.
To showcase the model’s capabilities, the residential building stock of Gothenburg City is used as a case study, and eight building materials are tracked. Environmental impacts (A1-A3) are calculated with embodied carbon factors. The main parameters are explored in a baseline scenario. Then, a second scenario focuses on a hypothetical policy that promotes improvements in building energy performance.
The simulation can be expanded to include more materials and built environment assets and allows for future explorations on, for example, the role of logistics, the implementation of recycling or reuse stations, and, in general, supporting sustainable and circular strategies from the construction sector.