Zooarchaeological evidences indicate that rabbit hunting became prevalent during the Upper Palaeolithic in the Iberian Peninsula.

The purpose of the ABM is to test if warren hunting using nets as a collective strategy can explain the introduction of rabbits in the human diet in the Iberian Peninsula during this period. It is analyzed whether this hunting strategy has an impact on human diet breadth by affecting the relative abundance of other main taxa in the dietary spectrum.
Model validity is measured by comparing simulated diet breadth to the observed diet breadth in the zooarchaeological record.

The agent-based model is explicitly grounded on the Diet Breadth Model (DBM), from the Optimal Foraging Theory (OFT).
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This model aims at creating agent populations that have “personalities”, as described by the Big Five Model of Personality. The expression of the Big Five in the agent population has the following properties, so that they resemble real life populations as closely as possible:
-The population mean of each trait is 0.5 on a scale from 0 to 1.
-The population-wide distribution of each trait approximates a normal distribution.
-The intercorrelations of the Big Five are close to those observed in the Literature.

The literature used to fit the model was a publication by Dimitri van der Linden, Jan te Nijenhuis, and Arnold B. Bakker:
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This model has been developed together with the publication ‘Modelling Value Change - An Exploratory Approach’

Value change and moral change have increasingly become topics of interest in the philosophical literature. Several theoretical accounts have been proposed. Such accounts are usually based on certain theoretical and conceptual assumptions and their strengths and weaknesses are often hard to determine and compare, also because they are based on limited empirical evidence.

We propose that a step forward can be made with the help of agent-based modelling (ABM). ABM can be used to investigate whether a simulation model based on a specific account of value change can reproduce relevant phenomena. To illustrate this approach, we built a model based on the pragmatist account of value change proposed in van de Poel and Kudina (2022). We show that this model can reproduce four relevant phenomena, namely 1) the inevitability and stability of values, 2) how different societies may react differently to external shocks, 3) moral revolutions, and 4) lock-in.

According to the philosopher of science K. Popper “All life is problem solving”. Genetic algorithms aim to leverage Darwinian selection, a fundamental mechanism of biological evolution, so as to tackle various engineering challenges.
Flibs’NFarol is an Agent Based Model that embodies a genetic algorithm applied to the inherently ill-defined “El Farol Bar” problem. Within this context, a group of agents operates under bounded rationality conditions, giving rise to processes of self-organization involving, in the first place, efficiency in the exploitation of available resources. Over time, the attention of scholars has shifted to equity in resource distribution, as well. Nowadays, the problem is recognized as paradigmatic within studies of complex evolutionary systems.
Flibs’NFarol provides a platform to explore and evaluate factors influencing self-organized efficiency and fairness. The model represents agents as finite automata, known as “flibs,” and offers flexibility in modifying the number of internal flibs states, which directly affects their behaviour patterns and, ultimately, the diversity within populations and the complexity of the system.

This ABM simulates problem solving agents as they work on a set of tasks. Each agent has a trait vector describing their skills. Two agents might form a collaboration if their traits are similar enough. Tasks are defined by a component vector. Agents work on tasks by decreasing tasks’ component vectors towards zero.

The simulation generates agents with given intrapersonal functional diversity (IFD), and dominant function diversity (DFD), and a set of random tasks and evaluates how agents’ traits influence their level of communication and the performance of a team of agents.

Modeling results highlight the importance of the distributions of agents’ properties forming a team, and suggests that for a thorough description of management teams, not only diversity measures based on individual agents, but an aggregate measure is also required.

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WeDiG Sim- Weighted Directed Graph Simulator - is an open source application that serves to simulate complex systems. WeDiG Sim reflects the behaviors of those complex systems that put stress on scale-free, weightedness, and directedness. It has been implemented based on “WeDiG model” that is newly presented in this domain. The WeDiG model can be seen as a generalized version of “Barabási-Albert (BA) model”. WeDiG not only deals with weighed directed systems, but also it can handle the […]

RaMDry allows to study the dynamic use of forage ressources by herbivores in semi-arid savanna with an emphasis on effects of change of climate and management. Seasonal dynamics affects the amount and the nutritional values of the available forage.

The purpose of the model is to simulate the spatial dynamics of potato late blight to analyse whether resistant varieties can be used effectively for sustainable disease control. The model represents an agricultural landscape with potato fields and data of a Dutch agricultural region is used as input for the model. We simulated potato production, disease spread and pathogen evolution during the growing season (April to September) for 36 years. Since late blight development and crop growth is weather dependent, measured weather data is used as model input. A susceptible and late blight resistant potato variety are distinguished. The resistant variety has a potentially lower yield but cannot get infected with the disease. However, during the growing season virulent spores can emerge as a result of mutations during spore production. This new virulent strain is able to infect the resistant fields, resulting in resistance breakdown. The model shows how disease severity, resistance durability and potato yield are affected by the fraction of fields across a landscape with a disease-resistant potato variety.

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.

Inspired by the European project called GLODERS that thoroughly analyzed the dynamics of extortive systems, Bottom-up Adaptive Macroeconomics with Extortion (BAMERS) is a model to study the effect of extortion on macroeconomic aggregates through simulation. This methodology is adequate to cope with the scarce data associated to the hidden nature of extortion, which difficults analytical approaches. As a first approximation, a generic economy with healthy macroeconomics signals is modeled and validated, i.e., moderate inflation, as well as a reasonable unemployment rate are warranteed. Such economy is used to study the effect of extortion in such signals. It is worth mentioning that, as far as is known, there is no work that analyzes the effects of extortion on macroeconomic indicators from an agent-based perspective. Our results show that there is significant effects on some macroeconomics indicators, in particular, propensity to consume has a direct linear relationship with extortion, indicating that people become poorer, which impacts both the Gini Index and inflation. The GDP shows a marked contraction with the slightest presence of extortion in the economic system.