The model explores how corruption may spread endogenously within a closed society by depicting the behavior within a cellular automaton context (CA) between bureaucrats and citizens. Within the model, corruption is characterized as a behavior product dependent upon an individual’s personal disposition towards honesty, rational decisionmaking processes, and neighbors’ behavior.

The model simulates seven agents engaging in collective action and inter-network social learning. The objective of the model is to demonstrate how mental models of agents can co-evolve through a complex relationship among factors influencing decision-making, such as access to knowledge and personal- and group-level constraints.

This NetLogo model simulates the spread of climate change beliefs within a population of individuals. Each believer has an initial belief level, which changes over time due to interactions with other individuals and exposure to media. The aim of the model is to identify possible methods for reducing climate change denial.

This BNE-informed ABM ultimately aims to provide a more realistic description of complicated pedestrian behaviours especially in high-density and life-threatening situations. Bayesian Nash Equilibrium (BNE) was adopted to reproduce interactive decision-making process among rational and game-playing agents. The implementations of 3 behavioural models, which are Shortest Route (SR) model, Random Follow (RF) model, and BNE model, make it possible to simulate emergent patterns of pedestrian behaviours (e.g. herding and self-organised queuing behaviours, etc.) in emergency situations.

According to the common features of previous mass trampling accidents, a series of simulation experiments were performed in space with 3 types of barriers, which are Horizontal Corridors, Vertical Corridors, and Random Squares, standing for corridors, bottlenecks and intersections respectively, to investigate emergent behaviours of evacuees in varied constricted spatial environments. The output of this ABM has been available at https://data.mendeley.com/datasets/9v4byyvgxh/1.

The FRAMe (Flood Resilience Agent-Based Model) serves as a framework designed to simulate flood resilience dynamics at the community level, focusing on a rural settlement in the Mekong River Basin. Integrating empirical data from extensive surveys, Bayesian networks, and hydrological simulations, the framework quantifies resilience as a trade-off between robustness (resistance to damage) and adaptability (capacity for dynamic response). Agents include households, governments, and other actors, linked by social and governance networks that facilitate knowledge transfer, resource distribution, and risk communication. FRAMe incorporates mechanisms for flood forecasting, policy interventions (education, aid, insurance), and individual and collective decision-making, grounded in Protection Motivation Theory and MoHuB frameworks. The framework’s spatially explicit design leverages GIS data, which supports scenario testing of governance structures and stakeholder interactions. By examining policy scenarios and agent behavior, FRAMe aims to inform adaptive flood management strategies and enhance community resilience.

The purpose of Hegmon’s Sharing model is to develop an understanding of the effect sharing strategies have on household survival.

A replication in Netlogo 5.2 of the classic model, Sugarscape (Epstein & Axtell, 1996).

Hydroman is a flexible spatially explicit model coupling human and hydrological processes to explore shallow water tables and land cover interactions in flat agricultural landscapes, modeled after the Argentine Pampas. Hydroman aligned well with established hydrological models, and was validated with water table patterns and crop yield observed in the study area.

Patagonia PSMED is an agent-based model designed to study a simple case of Evolution of Ethnic Differentiation. It replicates how can hunter-gatherer societies evolve and built cultural identities as a consequence of the way they interacted.

The CONSERVAT model evaluates the effect of social influence among farmers in the Lake Naivasha basin (Kenya) on the spatiotemporal diffusion pattern of soil conservation effort levels and the resulting reduction in lake sedimentation.