This code simulates individual-level, longitudinal substance use patterns that can be used to understand how cross-sectional U-shaped distributions of population substance use emerge. Each independent computational object transitions between two states: using a substance (State 1), or not using a substance (State 2). The simulation has two core components. Component 1: each object is assigned a unique risk factor transition probability and unique protective factor transition probability. Component 2: each object’s current decision to use or not use the substance is influenced by the object’s history of decisions (i.e., “path dependence”).

A dynamic identity model for misinformation in social networks, an agent-based model of social identity and misinformation dynamics.

I developed this model as a part of my master’s thesis, “Does social identity drive belief and persistence in online misinformation? An agent-based modelling approach” at University College Dublin, Ireland (2024-2025).

The purpose of this model is to further understand the dynamics of misinformation sharing as an expression of social identity. I introduce a framework to understand the influence of self-categorisation on misinformation persistence in social network. It integrates a social learning model with the Dynamic Identity Model for Agents (DIMA) using simple logic to simulate the social trade-offs driving misinformation and observe the effects on misinformation spread.

Three policy scenarios for urban expansion under the influences of the behaviours and decision modes of four agents and their interactions have been applied to predict the future development patterns of the Guangzhou metropolitan region.

Exploring how learning and social-ecological networks influence management choice set and their ability to increase the likelihood of species coexistence (i.e. biodiversity) on a fragmented landscape controlled by different managers.

This study employs a hierarchical cross-departmental ABM to explore the question: How and to what extent are the land use policies enforced when assessed against the real-world land use pattern? Specifically, two sub-questions are of interest: How can real-world policy interactions be abstracted into the behavior across hierarchical governmental departments in the model? How can the level of enforcement for each land use policy be quantified under these interactions? We build three hierarchical agents—the central level, the local level that incorporates three departments, and the village collective level—with simplified but plausible processes of land use change, with levels of enforcement of different land use policies as key parameters. We calibrate the model using a genetic algorithm to determine those parameters and answer our research question. We further applied the model to simulate potential land use changes and investigate the implications of different policy options. The results are expected to provide insights into the intricate relationships shaping land use processes, contributing to evidence-based decision-making in urban planning and sustainable land use management.

Package for simulating the behavior of experts in a scientific-forecasting competition, where the outcome of experiments itself depends on expert consensus. We pay special attention to the interplay between expert bias and trust in the reward algorithm. The package allows the user to reproduce results presented in arXiv:2305.04814, as well as testing of other different scenarios.

Simulates the construction of scientific journal publications, including authors, references, contents and peer review. Also simulates collective learning on a fitness landscape. Described in: Watts, Christopher & Nigel Gilbert (forthcoming) “Does cumulative advantage affect collective learning in science? An agent-based simulation”, Scientometrics.

Must tax-benefit policy making be limited to the ‘experts’?

An Agent-based model simulates consumer demand for Smart Metering tariffs. It utilizes the Bass Diffusion Model and Rogers´s adopter categories. Integration of empirical census microdata enables a validated socio-economic background for each consumer.

A System Dynamics Model to anticipate insurgent movements and policy design to handle them .