Criticality-Aware World Models for Complex System Societal Change Prediction Integrating A Unified Framework With RL, LLM, Multi-Expert Dynamics, Early Warning Signals, and Causal Counterfactual Reasoning

A new AI-driven, unified probabilistic framework improves crisis prediction in complex systems by combining specialized neural networks to detect phase transitions, heavy-tailed dynamics, and critical tipping points. The system integrates an LLM-powered news encoder, early warning signals, and causal counterfactual analysis for enhanced, uncertainty-aware forecasting.