MoPAgrIB model simulates the movement of cultivated patches in a savannah vegetation mosaic ; how they move and relocate through the landscape, depending on farming practices, population growth, social rules and vegetation growth.

We represent commuters and their preferences for transportation cost, time and safety. Agents assess their options via their preferences, their environment, and the modes available. The model has policy levers to test impact on last-mile problem.

The model aims at reproducing the evolution of the land-use in an agricultural territory at the plot scale. It enables to simulate the affectation of land-use, the crop rotation and technical operations for each plot of the different farms of the territory. It allows as well for crop farms to simulate the daily state of plots (sowed, plowed, harvested, biomass indicator). The model is used as an input for the water pollution model allowing to determine the flow of nitrate, phosphorus and suspended matter in the territory according to the landscape configuration.

a computer-based role-playing game simulating the interactions between farming activities, livestock herding and wildlife in a virtual landscape reproducing local socioecological dynamics at the periphery of Hwange National Park (Zimbabwe).

PopComp by Andre Costopoulos 2020
[email protected]
Licence: DWYWWI (Do whatever you want with it)

I use Netlogo to build a simple environmental change and population expansion and diffusion model. Patches have a carrying capacity and can host two kinds of populations (APop and BPop). Each time step, the carrying capacity of each patch has a given probability of increasing or decreasing up to a maximum proportion.

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Perpetual Motion Machine - A simple economy that operates at both a biophysical and economic level, and is sustainable. The goal: to determine the necessary and sufficient conditions of sustainability, and the attendant necessary trade-offs.

In 1985 Dr Michael Palmiter, a high school teacher, first built a very innovative agent-based model called “Simulated Evolution” which he used for teaching the dynamics of evolution. In his model, students can see the visual effects of evolution as it proceeds right in front of their eyes. Using his schema, small linear changes in the agent’s genotype have an exponential effect on the agent’s phenotype. Natural selection therefore happens quickly and effectively. I have used his approach to managing the evolution of competing agents in a variety of models that I have used to study the fundamental dynamics of sustainable economic systems. For example, here is a brief list of some of my models that use “Palmiter Genes”:
- ModEco - Palmiter genes are used to encode negotiation strategies for setting prices;
- PSoup - Palmiter genes are used to control both motion and metabolic evolution;
- TpLab - Palmiter genes are used to study the evolution of belief systems;
- EffLab - Palmiter genes are used to study Jevon’s Paradox, EROI and other things.

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This model is an agent-based simulation designed to explore how climate-induced environmental degradation can contribute to the emergence of social violence in coastal communities that depend heavily on ecosystem services for their livelihoods. The model represents a coupled social–ecological system in which environmental shocks—such as sea level rise and marine ecosystem decline—affect local economic conditions, food security, and community stability.

Agents in the model represent individuals whose livelihoods depend on coastal ecosystems. Environmental degradation reduces ecosystem productivity and increases economic hardship, which can lead to the formation of grievances among agents. The model incorporates behavioral thresholds that determine how individuals respond to hardship and perceived injustice. Under certain conditions—particularly when institutional capacity and law enforcement effectiveness are limited—these grievances may escalate into violent behavior.

The simulation allows users to explore how different climate scenarios, levels of ecosystem degradation, livelihood dependence, and institutional responses influence the probability of social instability and violence. By modeling the interactions between environmental stress, socio-economic vulnerability, and governance capacity, the model provides a computational framework for examining potential pathways linking climate change and conflict in coastal social–ecological systems.

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