Development repository for the Digital Terraria Lab implementation of the Sugarscape agent-based societal simulation.
A lean implementation of SugarScape in Python, optimized for experimentation
Stable, release-only repository for the Digital Terraria Lab implementation of the Sugarscape agent-based societal simulation.
Multi-agent simulation using LLMs. Agents autonomously decide actions for survival, reproduction, and social behavior in a grid world.This project aims to replicate a paper published in 2025 (arXiv:2508.12920).
A Python implementation of Epstein and Axtell's large scale agent-based computational model, the Sugarscape. Includes an implementation of Jeremy Bentham's Felicific Calculus as an option for decision-making.
An object-oriented representation of Axtell & Epstein's SugarScape written in Java. SugarScape is an artificially intelligent agent-based social simulation.
A Python implementation of Epstein and Axtell's large scale agent-based computational model, the Sugarscape, to explore the role of social phenomenon such as seasonal migrations, pollution, sexual reproduction, combat, trade, culture, and transmission of disease.
Evaluation of strategies in an economic landscape
🌐 Explore AI behaviors in a Sugarscape simulation, revealing insights into cooperation and survival instincts using Grok-4-Fast agents.
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