Patent Filing: Continuation B Escalation Control

Continuation B — Escalation Control introduces a patent-pending framework for halting runaway execution in multi-agent AI systems. Rather than relying on policy alignment, voting logic, or heuristic consensus, this architecture enforces structural termination when conflict resolution becomes impossible. It monitors agent disagreement persistence, recursive justification loops, and marginal information gain across execution cycles. When novelty collapses or disagreement thresholds are breached, the system halts autonomously — without requiring user intervention or external override. This continuation expands the Volition-Bound AI architecture into distributed, generative, and recursive agent ecosystems, ensuring AI systems can stop themselves when internal resolution structurally fails. ⚖️ Disclosure Notice This repository constitutes a public technical disclosure of an invention for the purpose of establishing prior art under applicable patent and intellectual property frameworks. The disclosure is intended to prevent subsequent patenting of substantially similar subject matter by other entities. This publication is timestamped and made permanently available via public archival platforms, including Zenodo, GitHub, and IPFS/Pinata, to preserve authorship attribution and document the structural origin of the disclosed invention. 📄 License This repository is published for disclosure and reference purposes only.No license to implement, reproduce, or commercialize the disclosed invention is granted by this publication.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-13
DOI
https://doi.org/10.5281/zenodo.18236655
Primary Topic
Reinforcement Learning in Robotics
Type
article
Field-Weighted Citation Impact
0.00
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article

Patent Filing: Continuation B Escalation Control

Sean Honan, Lucid The Forge
Zenodo (CERN European Organization for Nuclear Research)
Reinforcement Learning in Robotics
article

Patent Filing: Continuation B Escalation Control

Sean Honan, Lucid The Forge
article en

Abstract

Continuation B — Escalation Control introduces a patent-pending framework for halting runaway execution in multi-agent AI systems. Rather than relying on policy alignment, voting logic, or heuristic consensus, this architecture enforces structural termination when conflict resolution becomes impossible. It monitors agent disagreement persistence, recursive justification loops, and marginal information gain across execution cycles. When novelty collapses or disagreement thresholds are breached, the system halts autonomously — without requiring user intervention or external override. This continuation expands the Volition-Bound AI architecture into distributed, generative, and recursive agent ecosystems, ensuring AI systems can stop themselves when internal resolution structurally fails. ⚖️ Disclosure Notice This repository constitutes a public technical disclosure of an invention for the purpose of establishing prior art under applicable patent and intellectual property frameworks. The disclosure is intended to prevent subsequent patenting of substantially similar subject matter by other entities. This publication is timestamped and made permanently available via public archival platforms, including Zenodo, GitHub, and IPFS/Pinata, to preserve authorship attribution and document the structural origin of the disclosed invention. 📄 License This repository is published for disclosure and reference purposes only.No license to implement, reproduce, or commercialize the disclosed invention is granted by this publication.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 89%
Reinforcement Learning in Robotics
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