666ghj/MiroFish

Traditional prediction methods (statistical models, single-agent LLMs) fail to capture emergent collective behavior arising from individual interactions. MiroFish solves this by simulating large-scale agent societies with long-term memory and behavioral logic, allowing dynamic variable injection to explore 'what-if' scenarios at zero risk. It democratizes complex social simulation, making it accessible to non-experts via natural language inputs.

Developers can build applications for public opinion forecasting, policy impact analysis, financial signal prediction, and creative narrative generation (e.g., deducing lost novel endings). The ceiling includes creating fully interactive digital twins of real-world communities, enabling real-time decision rehearsal for organizations, and generating rich, emergent storylines for entertainment. The framework supports both macro-level strategic planning and micro-level playful simulations, with a live demo showcasing trending event prediction.