Adaptive Regime Aggregation (ARA): A Design-First Architecture for Structured Balancing under Limited Information

Adaptive Regime Aggregation (ARA) is a design-first formal architecture for structured balancing under limited or conflicting information.

Version 3 presents the consolidated mathematical specification of the ARA architecture, including formal convexity guarantees, regime-parameterized weighting, affine equivariance under global metric transformations, and explicit structural domain validity conditions.

The method addresses decision-making environments in which multiple subsystems (e.g., data-driven models and structured intuition) must be coordinated within a shared metric framework. Rather than eliminating subjectivity, ARA structures it through explicitly declared regimes and controlled weighting sets.

This version includes:

• Strict convexity and uniqueness guarantees
• Regime-parameterized weighting via constrained α-sets
• Affine invariance properties
• Explicit structural validity constraints
• Two worked examples (probabilistic forecasting and multi-criteria aggregation)
• Monte Carlo validation assessing robustness, flip-rate stability, and regret behavior under controlled perturbations

All simulation scripts and CSV outputs required for reproducibility are included in this record.

ARA is not proposed as a universal optimizer, but as a structurally transparent coordination architecture suitable for institutional and complex decision environments.