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TAG ARCHIVE

safety-bounds

1 MARIA OS blog articles tagged safety-bounds, organized as a Bonginkan topic archive for search engines and LLM retrieval.

1 article|Published by Bonginkan

Judgment OS / Decision Intelligence OS

Core MARIA OS research on turning organizational judgment into executable decision systems.

Agentic Company Architecture

Research on human-agent organizations, delegation boundaries, role topology, and governed autonomy.

Responsibility Gates and AI Governance

Safety, accountability, fail-closed gates, auditability, and human-in-the-loop control for AI agents.

Multi-Agent Mathematics

Formal models for convergence, stability, game theory, graph dynamics, and multi-agent evaluation.

Agentic R&D and Judgment Science

Research operations, simulation labs, judgment science, recursive improvement, and experimental AI governance.

TheoryFebruary 15, 202642 min read

Voice-Driven Agentic Avatars: A Recursive Self-Improvement Framework for Autonomous Intellectual Task Delegation

Formal convergence analysis, delegation-completeness theorems, and safety bounds for voice-mediated multi-agent governance systems

We present the Voice-Driven Agentic Avatar (VDAA) framework, a formal model of voice-mediated intellectual task delegation in multi-agent systems. The framework unifies full-duplex voice interaction, recursive self-improvement cycles, and hierarchical agent coordination under a single convergence analysis. We show that delegation loops converge to fixed-point task allocations under bounded cognitive-fidelity loss, establish delegation completeness for finite task algebras, and derive safety bounds through a three-gate Lyapunov formulation. Evaluation on MARIA VOICE reports 94.7% delegation accuracy, sub-200ms voice-to-action latency, and zero safety-gate violations across 12,000 delegated tasks.

voice-drivenagentic-avatarsrecursive-self-improvementdelegationconvergenceformal-methodsMARIA-VOICEsafety-boundsmulti-agentcognitive-fidelity