MiroFish — Predicting the Future by Simulating Thousands of AI Agents

Digital petri dishes

What happens when you release thousands of AI agents into a digital world and let them interact? MiroFish starts from this question.

How it works

Traditional ML learns patterns from historical data. MiroFish takes a different path. It gives LLM-powered agents distinct personalities, memories, and behavioral patterns, then lets them interact in simulated environments.

The emergent patterns from thousands of agents' collective behavior become predictions. Forecasting through social dynamics simulation.

Numbers

• GitHub Trending #1 (March 7)
• 28,600 stars
• +2,782 stars in 24 hours

Why it matters

Agent-based simulation is one of AI's next frontiers. Instead of single-model reasoning, it extracts insights from collective behavior of many agents. High potential for finance, policy, and social phenomenon prediction.