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.

…

This is a set of threshold public goods games models. Set consists of baseline model, endogenous shared punishment model, endogenous shared punishment model with activists and cooperation model. In each round, all agents are granted a budget of size set in GUI. Then they decide on how much they contribute to public goods and how much they keep. Public goods are provided only if the sum of contributions meets or exceeds the threshold defined in the GUI. After each round agents evaluate their strategy and payoff from this strategy.

the model can be used to describe the product diffusion in an Advance Selling Strategy. this model takes into account the consumers product adoption, and describe consumer’s online behavior based on four states.

On July 20th, James Holmes committed a mass shooting in a midnight showing of The Dark Knight Rises. The Aurora Colorado shooting was used as a test case to validate this framework for modeling mass shootings.

Designed to capture the evolutionary forces of global society.

A friendship game is a kind of network game: a game theory model on a network. This is a NetLogo model of an agent-based adaptation of “‘Friendship-based’ Games” by PJ Lamberson. The agents reach an equilibrium that depends on the strategy played and the topology of the network.

MERCURY aims to represent and explore two descriptive models of the functioning of the Roman trade system that aim to explain the observed strong differences in the wideness of distributions of Roman tableware.

RAGE models a stylized common property grazing system. Agents follow a certain behavioral type. The model allows analyzing how household behavior with respect to a social norm on pasture resting affects long-term social-ecological system dynamics.

DARTS simulates food systems in which agents produce, consume and trade food. Here, food is a summary item that roughly corresponds to commodity food types (e.g. rice). No other food types are taken into account. Each food system (World) consists of its own distribution of agents, regions and connections between agents. Agents differ in their ability to produce food, earn off-farm income and trade food. The agents aim to satisfy their food requirements (which are fixed and equal across agents) by either their own food production or by food purchases. Each simulation step represents one month, in which agents can produce (if they have productive capacity and it is a harvest month for their region), earn off-farm income, trade food (both buy and sell) and consume food. We evaluate the performance of the food system by averaging the agents’ food satisfaction, which is defined as the ratio of the food consumed by each agent at the end of each month divided by her food requirement. At each step, any of the abovementioned attributes related to the agents’ ability to satisfy their food requirement can (temporarily) be shocked. These shocks include reducing the amount of food they produce, removing their ability to trade locally or internationally and reducing their cash savings. Food satisfaction is quantified (both immediately after the shock and in the year following the shock) to evaluate food security of a particular food system, both at the level of agent types (e.g. the urban poor and the rural poor) and at the systems level. Thus, the effects of shocks on food security can be related to the food system’s structure.

Background: Establishing a human settlement on Mars is an incredibly complex engineering problem. The inhospitable nature of the Martian environment requires any habitat to be largely self-sustaining. Beyond mining a few basic minerals and water, the colonizers will be dependent on Earth resupply and replenishment of necessities via technological means, i.e., splitting Martian water into oxygen for breathing and hydrogen for fuel. Beyond the technical and engineering challenges, future colonists will also face psychological and human behavior challenges.
Objective: Our goal is to better understand the behavioral and psychological interactions of future Martian colonists through an Agent-Based Modeling (ABM simulation) approach. We seek to identify areas of consideration for planning a colony as well as propose a minimum initial population size required to create a stable colony.
Methods: Accounting for engineering and technological limitations, we draw on research regarding high performing teams in isolated and high stress environments (ex: submarines, Arctic exploration, ISS, war) to include the 4 NASA personality types within the ABM. Interactions between agents with different psychological profiles are modeled at the individual level, while global events such as accidents or delays in Earth resupply affect the colony as a whole.
Results: From our multiple simulations and scenarios (up to 28 Earth years), we found that an initial population of 22 was the minimum required to maintain a viable colony size over the long run. We also found that the Agreeable personality type was the one more likely to survive.
Conclusion We developed a simulation with easy to use GUI to explore various scenarios of human interactions (social, labor, economic, psychological) on a future colony on Mars. We included technological and engineering challenges, but our focus is on the behavioral and psychological effects on the sustainability of the colony on the long run. We find, contrary to other literature, that the minimum number of people with all personality types that can lead to a sustainable settlement is in the tens and not hundreds.