Endogenous social transition from a high-corruption state to a low-corruption state, replication of Hammond 2009

Spatial explicit model of a rangeland system, based on Australian conditions, where grass, woody shrubs and fire compete fore resources. Overgrazing can cause the system to flip from a healthy state to an unproductive shrub state. With the model one can explore the consequences of different movement rules of the livestock on the resilience of the system.

The model is discussed in Introduction to Agent-Based Modeling by Marco Janssen. For more information see https://intro2abm.com/.

It is very difficult to model a sustainable intergenerational biophysical/financial economy. ModEco NLG is one of a series of models exploring the dynamics of sustainable economics – PSoup, ModEco, EiLab, OamLab, MppLab, TpLab, CmLab.

Model explains both the final state and the dynamics of the development process of the wine sector in the Małopolska region in Poland. Model admits heterogeneous agents (regular farms,large and small vineyards).

The model implements a model that reflects features of a rural hill village in Nepal. Key features of the model include water storage, social capital and migration of household members who then send remittances back to the village.

This model illustrates a positive ‘growth’ feedback loop in which the areal extent of an entity increases through time.

Multi-layer network agent-based model of the progression of the COVID19 infection, digital contact tracing

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

An agent-based simulation of a game of basketball. The model implements most components of a standard game of basketball. Additionally, the model allows the user to test for the effect of two separate cognitive biases – the hot-hand effect and a belief in the team’s franchise player.

Manipulate[
Module[{fDot, mDot, poly, roots, stableRoots, rStar, rIso,
endPointStar, endPointIso},(1. Define the System Dynamics)
fDot = phi1(f/m) - phi2(m/f);
mDot = mu1(f/m) - mu2(m/f);
(*2. Find the Equilibrium Ratio r=f/
…