FoxNet is an individual-based modelling framework that can be customised to generate high-resolution red fox Vulpes vulpes population models for both northern and southern hemispheres. FoxNet predicts red fox population dynamics, including responses to control and landscape productivity. Model landscapes (up to ~15,000 km^2 and bait layouts can be generated within FoxNet or imported as GIS layers.

If you use FoxNet, please cite:

Hradsky BA, Kelly L, Robley A, Wintle BA (in review). FoxNet: an individual-based modelling framework to support red fox management. Journal of Applied Ecology.

The purpose of this model is to illustrate the use of agent-based computational modelling in the study of the emergence of reputation and status beliefs in a population.

LimnoSES is a coupled system dynamics, agent-based model to simulate social-ecological feedbacks in shallow lake use and management.

An agent-based model of Thomas Kuhn’s Structure of Scientific Revolutions

Knowledge Space model of Opinion Dynamics.

This is a NetLogo version of Buhl et al.’s (2005) model of self-organised digging activity in ant colonies. It was built for a master’s course on self-organisation and its intended use is still educational. The ants’ behavior can easily be changed by toggling switches on the interface, or, for more advanced students, there is R code included allowing the model to be run and analysed through RNetLogo.

This model aims to investigate how different type of learning (social system) and disturbance specific attributes (ecological system) influence adoption of treatment strategies to treat the effects of ecological disturbances.

In the consumer advice network, users with connections can interact with each other, and the network topology will change during the opinion interaction. When the opinion distance from i to j is greater than the confidence threshold, the two consumers cannot exchange opinions, and the link between them will disconnect with probability DE. Then, a link from node i to node k is established with probability CE and node i learning opinion from node k.

The model simulates interaction between internal physiological factors (e.g. energy balance) and external social factors (e.g. competition level) underlying feeding and social interaction behaviour of commercially group-housed pigs.

This is the R code of the mathematical model that includes the decision making formulations for artificial agents. This code corresponds to equations 1-70 given in the paper “A Mathematical Model of The Beer Game”.