agent-based-social

What problem does it solve?

This Skill helps you model and study how macro-level social outcomes emerge from individual-level behaviors, such as segregation, opinion polarization, and contagion spread.

Core Features & Use Cases

• Agent-based social modeling with Mesa: implement grid-based and network-based agent simulations with measurable outcomes over time.
• Schelling segregation: simulate residential sorting and quantify happiness and segregation using a dissimilarity index.
• Opinion dynamics (bounded confidence/Deffuant-Weisbuch): model belief updates, track cluster formation, and compare parameter regimes (e.g., different epsilon values).
• Social contagion (SIR on networks): run SIR dynamics on a Watts-Strogatz small-world graph, estimate outbreak conditions via R₀, and plot epidemic curves.
• Parameter sweeps: systematically vary key parameters (e.g., homophily thresholds) and aggregate results to identify critical regimes.

Use case: you want to test how varying homophily in Schelling’s model changes segregation and agent happiness, then repeat the experiment across multiple runs to estimate mean and variance of outcomes.

Quick Start

Use the agent-based-social skill to run a Mesa Schelling segregation simulation and produce happiness and segregation metrics plus plots for a chosen grid size, density, and homophily threshold.