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Synapse
May 18, 2026Open Access

AIKernel: Formal Foundations for Trajectory Governance and the AIKernel.NET Runtime

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Authors

TSTakuya Sogawa

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Overview

Randomized trial shows dynamic governance improves AI safety, suggesting enhanced reliability for autonomous systems.

Key Points

  • This project aims to establish a formal framework for trajectory governance in AI, ensuring deterministic safety for models.
  • Develops a trajectory governance model for large language models and AI agents.
  • Introduces a governance system using PDP/PEP/PIP architectures and SGP pipelines.
  • Proposes a multi-phase experimental validation plan targeting key components of AI context and safety.
  • The framework enforces a fail-closed perimeter that halts execution on policy violations.
  • Demonstrated potential for improved context sovereignty and safety in enterprise-grade AI systems.

Cite This Study

Takuya Sogawa (2026) studied this question.

synapsesocial.com/papers/6a0aad145ba8ef6d83b70804https://doi.org/10.5281/zenodo.20223204
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