The aim of this model is to study the dynamic propagation of individual climate adaptive behaviours in different scenarios within the analytical framework of conservation motivation theory, focusing on the impact of social and experiential learning on the adoption of climate adaptive behaviours by coastal farmers.
Model for paper “Promoting climate resilience through learning-based behavioural change: Insights from an agent-based model of a coastal farming community in Guangxi, China” in Environmental Science & Policy, Volume 179, May 2026, 104375, https://doi.org/10.1016/j.envsci.2026.104375

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”).

The first simple movement models used unbiased and uncorrelated random walks (RW). In such models of movement, the direction of the movement is totally independent of the previous movement direction. In other words, at each time step the direction, in which an individual is moving is completely random. This process is referred to as a Brownian motion.
On the other hand, in correlated random walks (CRW) the choice of the movement directions depends on the direction of the previous movement. At each time step, the movement direction has a tendency to point in the same direction as the previous one. This movement model fits well observational movement data for many animal species.

The presented agent based model simulated the movement of the agents as a correlated random walk (CRW). The turning angle at each time step follows the Von Mises distribution with a ϰ of 10. The closer ϰ gets to zero, the closer the Von Mises distribution becomes uniform. The larger ϰ gets, the more the Von Mises distribution approaches a normal distribution concentrated around the mean (0°).
In this script the turning angles (following the Von Mises distribution) are generated based on the the instructions from N. I. Fisher 2011.
This model is implemented in Javascript and can be used as a building block for more complex agent based models that would rely on describing the movement of individuals with CRW.

This is the replication of the experiment performed by Eerkens and Lipo (2005) to look at the effect of copying errors when specific traits are transferred from an individual to another.

This model can be used to optimize intervention strategies for inspection services.

This is a simplified version of a Complex Model of Voter Turnout by Edmonds et al.(2014). It was developed to better understand the mechanisms at play on that complex model.

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

This model simulate product diffusion on different social network structures.

This model investigates how anti-conformist intentions could be related to some biases on the perception of attitudes. It starts from two case studies, related to the adoption of organic farming, that show anti-conformist intentions. It proposes an agent-based model which computes an intention based on the Theory of Reasoned Action and assumes some biases in the perception of others’ attitudes according to the Social Judgement Theory.
It investigates the conditions on the model parameter values for which the simulations reproduce the features observed in the case studies. The results suggest that perception biases are indeed likely to contribute to anti-conformist intentions.

An agent-based model of the Free/Libre Open Source Software (FLOSS) development process designed around agents selecting FLOSS projects to contribute to and/or download.