This model simulates how collective self-organisation among individuals that manage irrigation resource collectively.

A hybrid predator-prey model of fish and plankton that switches dynamically between ABM and SD representations. It contains 6 related structural designs of the same model.

This is an agent-based model designed to explore the evolution of cooperation under changes in resources availability for a given population

Project for the course “Introduction to Agent-Based Modeling”.

The NetLogo model implements an Opinion Dynamics model with different confidence distributions, inspired by the Bounded Confidence model presented by Hegselmann and Krause in 2002. Hegselmann and Krause used a model with uniform distribution of confidence, but one could imagine agents that are more confident in their own opinions than others. Confidence with triangular, semi-circular, and Gaussian distributions are implemented. Moreover, network structure is optional and can be taken into account in the agent’s confidence such that agents assign less confidence the further away from them other agents are.

Micro-targeted vs stochastic political campaigning agent-based model simulation. Written by Toby D. Pilditch (University of Oxford, University College London), in collaboration with Jens K. Madsen (University of Oxford, London School of Economics)

The purpose of the model is to explore the various impacts on voting intention among a population sample, when both stochastic (traditional) and Micto-targeted campaigns (MTCs) are in play. There are several stages of the model: initialization (setup), campaigning (active running protocols) and vote-casting (end of simulation). The campaigning stage consists of update cycles in which “voters” are targeted and “persuaded” - updating their beliefs in the campaign candidate / policies.

This computational model is an agent-based model (ABM) developed to investigate how repeated failures of emerging niches accumulate and influence the trajectory of socio-technical transitions. Built in AnyLogic 8.7.11, the model simulates the dynamic interactions between a dominant regime and sequential niche entrants within a two-dimensional practice space. It models alignment, movement, and competition based on technological maturity and market penetration. The model utilizes a reinforcing feedback structure linking consumer support, output, resource accumulation, and capacity development (Physical and Institutional Capacity). A complete model specification following the ODD+D (Overview, Design concepts, Details, and Decision) protocol is included in the documentation.

This model studies the effect of the agents’ adaptive expectation on cooperation frequency in the prisoner’s dilemma game in complex networks from an agent based approach. The model is implemented in Repast simphony 1.2.

We used a computer simulation to measure how well different network structures (fully connected, small world, lattice, and random) find and exploit resource peaks in a variable environment.

This model simulates movements of mobile pastoralists and their impacts on the transmission of foot-and-mouth disease (FMD) in the Far North Region of Cameroon.

Status-power dynamics on a playground, resulting in a status landscape with a gender status gap. Causal: individual (beauty, kindness, power), binary (rough-and-tumble; has-been-nice) or prior popularity (status). Cultural: acceptability of fighting.