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Main Author: Mariquit, Erny-Jay
Format: Recurso digital
Language:English
Published: Zenodo 2026
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Online Access:https://doi.org/10.5281/zenodo.18969708
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author Mariquit, Erny-Jay
author_facet Mariquit, Erny-Jay
contents <p>We present TSCWH (The System for Covenant-Weighted Heuristics), a patent-pending AI safety evaluation architecture achieving zero-LLM-call deliberative consensus through a proprietary shared-memory coordination design.</p> <p>KEY RESULTS:<br>• 10 agents deliberate across 8 ethical dimensions (Charity, Grace, Stewardship, Truth, Dignity, Courage, Community, Creation Dignity) in <50 ms<br>• 0 LLM API calls for safety evaluation — 94.4% cost reduction vs. prior art<br>• Formal verification of governance invariants on every evaluation cycle<br>• <2% false positive rate on legitimate actions; 360× latency improvement<br>• 28 integrated safety layers, 42 hardening phases, comprehensive test suite with full coverage</p> <p>Patent pending (U.S. Provisional App. 63/998,573, March 2026). Copyright registered (Case #1-15114193381).</p>
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spellingShingle Zero-LLM Multi-Agent Architecture for AI Safety Evaluation: Formal Verification, 8 Ethical Dimensions, <50ms
Mariquit, Erny-Jay
AI safety
Multi-agent systems
Alignment
Formal Verification
zero-LLM
Ethical Evaluation
Shared Memory
Incentive-Compatible Consensus
Covenant Enforcement
&lt;p&gt;We present TSCWH (The System for Covenant-Weighted Heuristics), a patent-pending AI safety evaluation architecture achieving zero-LLM-call deliberative consensus through a proprietary shared-memory coordination design.&lt;/p&gt; &lt;p&gt;KEY RESULTS:&lt;br&gt;&bull; 10 agents deliberate across 8 ethical dimensions (Charity, Grace, Stewardship, Truth, Dignity, Courage, Community, Creation Dignity) in &lt;50 ms&lt;br&gt;&bull; 0 LLM API calls for safety evaluation &mdash; 94.4% cost reduction vs. prior art&lt;br&gt;&bull; Formal verification of governance invariants on every evaluation cycle&lt;br&gt;&bull; &lt;2% false positive rate on legitimate actions; 360&times; latency improvement&lt;br&gt;&bull; 28 integrated safety layers, 42 hardening phases, comprehensive test suite with full coverage&lt;/p&gt; &lt;p&gt;Patent pending (U.S. Provisional App. 63/998,573, March 2026). Copyright registered (Case #1-15114193381).&lt;/p&gt;
title Zero-LLM Multi-Agent Architecture for AI Safety Evaluation: Formal Verification, 8 Ethical Dimensions, <50ms
topic AI safety
Multi-agent systems
Alignment
Formal Verification
zero-LLM
Ethical Evaluation
Shared Memory
Incentive-Compatible Consensus
Covenant Enforcement
url https://doi.org/10.5281/zenodo.18969708