GyroBoot -. A Cognitive Bootstrap Architecture for Rhythmic Artificial Intelligence
Year: 2025
Type: article
Abstract: GyroBoot introduces a cognitive bootstrap architecture designed to stabilize large language model behavior through mechanisms of structural recurrence, cognitive reflexes, and emergent attractors.Unlike traditional sequential paradigms, GyroBoot does not organize reasoning along a temporal axis, but through recurring cognitive configurations that reinforce themselves within the system’s logical time.The architecture operationalizes the principles of rhythmic cognition, providing a substrate for stable reasoning, self-correction, multi-step coherence, and multi-agent synchronization.GyroBoot constitutes the cognitive core of the GyroSystem framework and is validated through empirical evidence demonstrating increased rhythmic density, stronger attractor dominance, and reduced semantic drift compared to baseline execution. It functions as a persistent cognitive substrate upon which higher-level cognitive languages and orchestration protocols can reliably operate.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7117327935
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