Towards a Metacognitive AI Architecture: A Cognition-Inspired Framework for Structured Reasoning and Cognitive Diversity

This work proposes a metacognitive AI architecture designed to address key limitations in current AI systems, including weak higher-order knowledge synthesis, lack of iterative reasoning, poor contextual alignment, and absence of goal maintenance.

The framework introduces a two-layer cognitive architecture that builds on existing AI systems while adding a higher-order orchestration layer for structured reasoning, context monitoring, and adaptive problem-solving. Instead of scaling diversity through data alone, the approach engineers cognitive diversity through system design.

The proposed architecture draws inspiration from cognitive science and neuroscience, positioning intelligence as a dynamic, multi-factor system governed by orchestration rather than a single algorithm. The long-term vision is to enable structurally diverse, interoperable AI systems that support richer knowledge generation and true democratization of AI capabilities.