AIScientists-Dev/WorldSeed
📦 Open Source ProjectAIScientists-Dev
A sophisticated multi-agent world engine where autonomous AI agents live, interact, and exhibit emergent social behaviors.
WorldSeed is a high-fidelity multi-agent world engine designed to facilitate the study of emergent behavior in autonomous AI systems. Unlike static agent benchmarks, WorldSeed provides a dynamic, persistent environment where agents possess memory, personality, and the ability to engage in complex social interactions. The engine utilizes LLMs to drive agent decision-making, allowing for natural language communication and strategic planning. Key technical features include a modular architecture that supports diverse agent configurations, a robust event-driven simulation loop, and tools for tracking agent relationships and societal evolution over time. By simulating 'more is different' phenomena, the project allows users to observe how individual agent goals aggregate into complex, unpredictable group dynamics. It is built with a Python-based backend, making it accessible for AI researchers looking to integrate custom agent models or experiment with multi-agent coordination strategies in a sandbox setting.
💡Highlights
- ├─Persistent multi-agent simulation
- ├─LLM-driven social interaction
- └─Emergent behavior modeling
🎯For
- ├─AI Researchers
- ├─Multi-agent Systems Developers
- └─Game AI Engineers