This paper presents a novel architecture for artificial general intelligence (AGI) systems designed to harmonize conflicting objectives in real time under conditions of uncertainty. Drawing inspiration from orchestral metaphors and adaptive control theory, we propose a multi-layered goal-orchestration framework that enables AGI to prioritize, balance, and revise goals dynamically. Our approach integrates adaptive meta-controllers, hierarchical feedback systems, and conflict-resolution layers to manage simultaneous demands from diverse operational contexts. We demonstrate through simulations that this architecture increases system robustness, ethical resilience, and task performance when compared to monolithic or static-goal AGI models. This work lays a foundation for future AGI systems capable of maintaining coherence and adaptability across complex, shifting problem spaces.

Keywords: AGI; adaptive orchestration; conflicting objectives; goal harmonization; dynamic control; uncertainty management

Subject: Adaptive AGI Architectures

https://github.com/rfigurelli/Trajecta-AI-Labs/blob/main/The%20Symphony%20of%20Uncertainty.md