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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AGENTS model is an agent-based computational framework designed to explore the socio-ecological and economic dynamics of agricultural production in the Byzantine Negev Highlands, with a focus on viticulture. It integrates historical, environmental, and social factors to simulate settlement sustainability, crop yields, and the impacts of varying climate conditions. The model is built in NetLogo and incorporates GIS-based topographical and hydrological data. Key features include the ability to assess climate impacts on crop profitability and settlement strategies, evaluate economic outputs of ancient vineyards, and simulate agent decision-making processes under diverse scenarios.

The AGENTS model is highly flexible, enabling users to simulate agricultural regimes with any two crops: one cash crop (a crop grown for profit, e.g., grapevines) and one staple crop (a crop grown for subsistence, e.g., wheat). While the default setup models viticulture and wheat cultivation in the Byzantine Negev Highlands, users can adapt the model to different environmental and socio-ecological contexts worldwide—both past and present.

Users can load external files to customize precipitation, evaporation, topography, and labor costs (measured as man-days per 0.1ha, converted to kg of wheat per model patch size area), and can also edit key parameters related to yield calculations. This includes modifying crop-specific yield formulas, soil and runoff indices, and any factors influencing crop performance. The model inherently simulates cash crops grown in floodplain regions and staple crops cultivated along riverbanks, providing a powerful tool to investigate societal resilience and responses to climate stressors across diverse environments.

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This repository contains an agent-based simulation model exploring how status hierarchies influence the emergence and sustainability of cooperation in task-oriented groups. The model builds on evolutionary game theory to examine the dynamics of cooperation under single-leader and multi-leader hierarchies, investigating factors such as group size, assortativity, and hierarchical clarity. Key findings highlight the trade-offs between different leadership structures in fostering group cooperation and reveal the conditions under which cooperation is most stable.

The repository includes code for simulations, numerical analysis scripts, and visualization tools to replicate the results presented in the manuscript titled “Status hierarchies and the emergence of cooperation in task groups.”

Feel free to explore, reproduce the findings, or adapt the model for further research!

ViSA 2.0.0 is an updated version of ViSA 1.0.0 aiming at integrating empirical data of a new use case that is much smaller than in the first version to include field scale analysis. Further, the code of the model is simplified to make the model easier and faster. Some features from the previous version have been removed.
It simulates decision behaviors of different stakeholders showing demands for ecosystem services (ESS) in agricultural landscape. It investigates conditions and scenarios that can increase the supply of ecosystem services while keeping the viability of the social system by suggesting different mixes of initial unit utilities and decision rules.

ViSA simulates the decision behaviors of different stakeholders showing demands for ecosystem services (ESS) in agricultural landscape. The lack of sufficient supply of ESSs triggers stakeholders to apply different management options to increase their supply. However, while attempting to reduce the supply-demand gap, conflicts arise among stakeholders due to the tradeoff nature of some ESS. ViSA investigates conditions and scenarios that can minimize such supply-demand gap while reducing the risk of conflicts by suggesting different mixes of management options and decision rules.

This model has been created with and for the researcher-farmers of the Muonde Trust (http://www.muonde.org/), a registered Zimbabwean non-governmental organization dedicated to fostering indigenous innovation. Model behaviors and parameters (mashandiro nemisiyano nedzimwe model) derive from a combination of literature review and the collected datasets from Muonde’s long-term (over 30 years) community-based research. The goals of this model are three-fold (muzvikamu zvitatu):
A) To represent three components of a Zimbabwean agro-pastoral system (crops, woodland grazing area, and livestock) along with their key interactions and feedbacks and some of the human management decisions that may affect these components and their interactions.
B) To assess how climate variation (implemented in several different ways) and human management may affect the sustainability of the system as measured by the continued provisioning of crops, livestock, and woodland grazing area.
C) To provide a discussion tool for the community and local leaders to explore different management strategies for the agro-pastoral system (hwaro/nzira yekudyidzana kwavanhu, zvipfuo nezvirimwa), particularly in the face of climate change.

The purpose of the study is to unpack and explore a potentially beneficial role of sharing metacognitive information within a group when making repeated decisions about common pool resource (CPR) use.

We explore the explanatory power of sharing metacognition by varying (a) the individual errors in judgement (myside-bias); (b) the ways of reaching a collective judgement (metacognition-dependent), (c) individual knowledge updating (metacognition- dependent) and d) the decision making context.

The model (AgentEx-Meta) represents an extension to an existing and validated model reflecting behavioural CPR laboratory experiments (Schill, Lindahl & Crépin, 2015; Lindahl, Crépin & Schill, 2016). AgentEx-Meta allows us to systematically vary the extent to which metacognitive information is available to agents, and to explore the boundary conditions of group benefits of metacognitive information.

The agent-based perspective allows insights on how behaviour of firms, guided by simple economic rules on the micro-level, is dynamically influenced by a complex environment in regard to the assumed relocation, decision-making hypotheses. Testing various variables sensitive to initial conditions, increased environmental regulations targeting global trade and upward shifting wage levels in formerly offshore production locations have shown to be driving and inhibiting mechanisms of this socio-technical system. The dynamic demonstrates a shift from predominantly cited economic reasoning for relocation strategies towards sustainability aspects, pressingly changing these realities on an environmental and social dimension. The popular debate is driven by increased environmental awareness and the proclaimed fear of robots killing jobs. In view of reshoring shaping the political agenda, interest in the phenomenon has recently been fuelled by the rise of populism and protectionism.

The model investigates conditions, scenarios and strategies for future planning of energy in Egypt, with an emphasis on alternative energy pathways and a sustainable electricity supply mix as part of an energy roadmap till the year 2100. It combines the multi-criteria decision analysis (MCDA) with agent-based modeling (ABM) and Geographic Information Systems (GIS) visualization to integrate the interactions of the decisions of multi-agents, the multi-criteria evaluation of sustainability, the time factor and the site factors to assess the transformation of energy landscapes.

This NetLogo model illustrates the cultural evolution of pro-environmental behaviour patterns. It illustrates how collective behaviour patterns evolve from interactions between agents and agents (in a social network) as well as agents and the affordances (action opportunities provided by the environment) within a niche. More specifically, the cultural evolution of behaviour patterns is understood in this model as a product of:

1. The landscape of affordances provided by the material environment,
2. Individual learning and habituation,
3. Social learning and network structure,
4. Personal states (such as habits and attitudes), and
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