The emergence of cooperation in human societies is often linked to environmental constraints, yet the specific conditions that promote cooperative behavior remain an open question. This study examines how resource unpredictability and spatial dispersion influence the evolution of cooperation using an agent-based model (ABM). Our simulations test the effects of rainfall variability and resource distribution on the survival of cooperative and non-cooperative strategies. The results show that cooperation is most likely to emerge when resources are patchy, widely spaced, and rainfall is unpredictable. In these environments, non-cooperators rapidly deplete local resources and face high mortality when forced to migrate between distant patches. In contrast, cooperators—who store and share resources—can better endure extended droughts and irregular resource availability. While rainfall stochasticity alone does not directly select for cooperation, its interaction with resource patchiness and spatial constraints creates conditions where cooperative strategies provide a survival advantage. These findings offer broader insights into how environmental uncertainty shapes social organization in resource-limited settings. By integrating ecological constraints into computational modeling, this study contributes to a deeper understanding of the conditions that drive cooperation across diverse human and animal systems.

This abstract model explores the emergence of altruistic behavior in networked societies. The model allows users to experiment with a number of population-level parameters to better understand what conditions contribute to the emergence of altruism.

This model simulates the heterogeneity of preferences in a PG game and how the interaction between them affects the dynamics of voluntary contributions. Model is based on the results of a human-based experiment.

This is the code for the model described in an article in the International Journal of Microsimulation. Lawson (2013) ‘Modelling Household Spending Using a Random Assignment Scheme’, International Journal of Microsimulation, 6(2) Autumn 2013, 56-75.

A model of attitudinal dynamics based on the cognitive mechanism of emotional coherence. The code is written in Java. For initialization an additional dataset is required.

We propose an ABM replicating the evolution of action oriented groups (like NPO) due to disagreement among members on the practices to implement. Looking at the stability and representativeness (ability of groups to federate) we introduce vertical communication: the possibility for group to communicate around their practices to their members. We test for three levels (to whom it is addressed) and four types (how it influences agents) of communication.

We model interpersonal dynamics and study behavior in the classroom in the hypothetical case of a single teacher who defines students’ seating arrangements. The model incorporates the mechanisms of peer influence on study behavior, on attitude formation, and homophilous selection in order to depict the interrelated dynamics of networks, behavior, and attitudes. We compare various seating arrangement scenarios and observe how GPA distribution and level of prejudice changes over time.

This model is supporting the serious game RÁC (“waste” in Vietnamese), dedicated to foster discussion about solid waste management in a Vietnamese commune in the Bắc Hưng Hải irrigation system.
The model is replicating waste circulation and environmental impact in four fictive villages. During the game, the players take actions and see how their decisions have an impact on the model.
This model was implemented using the GAMA platform, using gaml language.

The present model was created and used for the study titled ``Agent-Based Insight into Eco-Choices: Simulating the Fast Fashion Shift.” The model is implemented in the multi-agent programmable environment NetLogo 6.3.0. The model is designed to simulate the behavior and decision-making processes of individuals (agents) in a social network. It focuses on how agents interact with their peers, social media, and government campaigns, specifically regarding their likelihood to purchase fast fashion.

BarterNet is a platform for modeling early barter networks with the aim of learning how supply and demand for a good determine if traders will learn to use that good as a form of money. Traders use a good as money when they offer to trade for it even if they can’t consume it, but believe that they can subsequently trade it for a good they can consume in the near future.