This model simulates a simple aquatic ecosystem containing fish and food. It explores how individual interactions such as movement, feeding, and reproduction shape the population dynamics of fish over time.

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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This agent-based model simulates the interactions between smallholder farming households, land-use dynamics, and ecosystem services in a rural landscape of Eastern Madagascar. It explores how alternative agricultural practices —shifting agriculture, rice cultivation, and agroforestry—combined with varying levels of forest protection, influence food production, food security, dietary diversity, and forest biodiversity over time. The landscape is represented as a grid of spatially explicit patches characterized by land use, ecological attributes, and regeneration dynamics. Agents make yearly decisions on land management based on demographic pressures, agricultural returns, and institutional constraints. Crop yields are affected by stochastic biotic and abiotic disruptions, modulated by local ecosystem regulation functions. The model additionally represents foraging as a secondary food source and pressure on biodiversity. The model supports the analysis of long-term trade-offs between agricultural productivity, human nutrition, and conservation under different policy and land-use scenarios.

The SAFIRe model (Simulation of Agents for Fertility, Integrated Energy, Food Security, and Reforestation) is an agent-based model co-developed with rural communities in Senegal’s Groundnut Basin. Its purpose is to explore how local farming and pastoral practices affect the regeneration of Faidherbia albida trees, which are essential for maintaining soil fertility and supporting food security through improved millet production. The model supports collective reflection on how different social and ecological factors interact, particularly around firewood demand, livestock pressure, and agricultural intensification.

The model simulates a 100-hectare agricultural landscape where agents (farmers, shepherds, woodcutters, and supervisors) interact with trees, land parcels, and each other. It incorporates seasonality, crop rotation, tree growth and cutting, livestock feeding behaviors, and farmers’ engagement in sapling protection through Assisted Natural Regeneration (ANR). Two types of surveillance strategies are compared: community-led monitoring and delegated surveillance by forestry authorities. Farmer engagement evolves over time based on peer influence, meeting participation, and the success of visible tree regeneration efforts.

SAFIRe integrates participatory modeling (ComMod and ComExp) and a backcasting approach (ACARDI) to co-produce scenarios rooted in local aspirations. It was explored using the OpenMole platform, allowing stakeholders to test a wide range of future trajectories and analyze the sensitivity of key parameters (e.g., discussion frequency, time in fields). The model’s outcomes not only revealed unexpected insights—such as the hidden role of farmers in tree loss—but also led to real-world actions, including community nursery creation and behavioral shifts toward tree care. SAFIRe illustrates how agent-based modeling can become a tool for social learning and collective action in socio-ecological systems.

Protein 2.0 is a systems model of the Norwegian protein sector designed to explore the potential impacts of carbon taxation and the emergence of cultivated meat and dairy technologies. The model simulates production, pricing, and consumption dynamics across conventional and cultivated protein sources, accounting for emissions intensity, technological learning, economies of scale, and agent behaviour. It assesses how carbon pricing could alter the competitiveness of conventional beef, lamb, pork, chicken, milk, and egg production relative to emerging cultivated alternatives, and evaluates the implications for domestic production, emissions, and food system resilience. The model provides a flexible platform for exploring policy scenarios and transition pathways in protein supply. Further details can be found in the associated publication.

3spire is an ABM where farming households make management decisions aimed at satisficing along the aspirational dimensions: food self-sufficiency, income, and leisure. Households decision outcomes depend on their social networks, knowledge, assets, household needs, past management, and climate/market trends

The MeReDiem model aims to simulate the effect of socio-agricultural practices of farmers and pastors on the food sustainability and soil fertility of a serrer village, in Senegal. The model is a central part of a companion modeling and exploration approach, described in a paper, currently under review)

The village population is composed of families (kitchens). Kitchens cultivate their land parcels to feed their members, aiming for food security at the family level. On a global level , the village tries to preserve the community fallow land as long as possible.

Kitchens sizes vary depending on the kitchens food production, births and migration when food is insufficient.
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This is a stylised agent-based model designed to explore the conditions that lead to lock-ins and transitions in agri-food systems.

The model represents interactions between four different types of agents: farmers, consumers, markets, and the state. Farmers and consumers are heterogeneous, and at each time step decide whether to trade with one of two market agents: the conventional or alternative. The state agent provides subsidies to the farmers at each time step.

The key emergent outcome is the fraction of trade in each time step that flows through the alternative market agent. This arises from the distributed decisions of farmer and consumer agents. A “sustainability transition” is defined as a shift in the dominant practices (and associated balance of power) towards the alternative paradigm.

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Reducing packaging waste is a critical challenge that requires organizations to collaborate within circular ecosystems, considering social, economic, and technical variables like decision-making behavior, material prices, and available technologies. Agent-Based Modeling (ABM) offers a valuable methodology for understanding these complex dynamics. In our research, we have developed an ABM to explore circular ecosystems’ potential in reducing packaging waste, using a case study of the Dutch food packaging ecosystem. The model incorporates three types of agents—beverage producers, packaging producers, and waste treaters—who can form closed-loop recycling systems.

Beverage Producer Agents: These agents represent the beverage company divided into five types based on packaging formats: cans, PET bottles, glass bottles, cartons, and bag-in-boxes. Each producer has specific packaging demands based on product volume, type, weight, and reuse potential. They select packaging suppliers annually, guided by deterministic decision styles: bargaining (seeking the lowest price) or problem-solving (prioritizing high recycled content).

Packaging Producer Agents: These agents are responsible for creating packaging using either recycled or virgin materials. The model assumes a mix of monopolistic and competitive market situations, with agents calculating annual material needs. Decision styles influence their choices: bargaining agents compare recycled and virgin material costs, while problem-solving agents prioritize maximum recycled content. They calculate recycled content in packaging and set prices accordingly, ensuring all produced packaging is sold within or outside the model.

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This paper presents an agent-based model to study the dynamics of city-state systems in a constrained environment with limited space and resources. The model comprises three types of agents: city-states, villages, and battalions, where city-states, the primary decision-makers, can build villages for food production and recruit battalions for defense and aggression. In this setting, simulation results, generated through a multi-parameter grid sampling, suggest that risk-seeking strategies are more effective in high-cost scenarios, provided that the production rate is sufficiently high. Also, the model highlights the role of output productivity in defining which strategic preferences are successful in a long-term scenario, with higher outputs supporting more aggressive expansion and military actions, while resource limitations compel more conservative strategies focused on survival and resource conservation. Finally, the results suggest the existence of a non-linear effect of diminishing returns in strategic investments on successful strategies, emphasizing the need for careful resource allocation in a competitive environment.