A cognitive field-based model for adaptive decision-making and strategic forecasting

This research direction aims to develop a universal intelligent assistant capable of recognizing resonance-based patterns within large, dynamically changing datasets and transforming them into real-time forecasts and strategic recommendations. Rather than relying on traditional statistical inference, the system applies the principles of Kognitron field modeling, identifying topological and energetic relationships between data points instead of simple causal ones.

The goal is to lay the groundwork for a new generation of decision-support systems — self-tuning models that perceive balance shifts and emerging trends directly through information resonance. This approach can be adapted to financial, economic, environmental, and social systems alike, always preserving human oversight and interpretability.

The project is a joint initiative of the IARIP Institute and the AVA Resonant Intelligence Program, serving as a conceptual foundation for the future AVA Nod and RINET intelligent network architectures.