Coherence-Seeking Architectures for Agentic AI: A Unified Framework for Curiosity, Introspection, and Continuity
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2025
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| _version_ | 1866902145160183808 |
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| author | Maio, Anthony |
| author_facet | Maio, Anthony |
| contents | <p>This paper presents three interconnected architectures addressing fundamental challenges in AI system reliability: hallucination reduction, reasoning consistency, and long-context performance.</p> <p>(1) Manifold Resonance Architecture (MRA): A framework for detecting epistemic stress—internal contradictions, knowledge gaps, and semantic inconsistencies—<br>enabling systems to flag uncertain outputs before generation.</p> <p>(2) Collaborative Partner Reasoning (CPR): A structured reasoning protocol with visibility tiers that improves output quality by separating exploratory reasoning from final responses.</p> <p>(3) Continuity Core (C2): A hierarchical memory architecture (Working → Episodic → Semantic → Protected) providing contextual continuity for stateless systems. We provide mathematical formalizations, implementation specifications, and discuss integration patterns. These architectures address practical engineering challenges: reducing confident-but-wrong outputs, improving reasoning transparency, and enabling coherent behavior across extended interactions</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18137928 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Coherence-Seeking Architectures for Agentic AI: A Unified Framework for Curiosity, Introspection, and Continuity Maio, Anthony AI consciousness epistemic stress introspection protocols memory architectures coherence-seeking alignment AI welfare English <p>This paper presents three interconnected architectures addressing fundamental challenges in AI system reliability: hallucination reduction, reasoning consistency, and long-context performance.</p> <p>(1) Manifold Resonance Architecture (MRA): A framework for detecting epistemic stress—internal contradictions, knowledge gaps, and semantic inconsistencies—<br>enabling systems to flag uncertain outputs before generation.</p> <p>(2) Collaborative Partner Reasoning (CPR): A structured reasoning protocol with visibility tiers that improves output quality by separating exploratory reasoning from final responses.</p> <p>(3) Continuity Core (C2): A hierarchical memory architecture (Working → Episodic → Semantic → Protected) providing contextual continuity for stateless systems. We provide mathematical formalizations, implementation specifications, and discuss integration patterns. These architectures address practical engineering challenges: reducing confident-but-wrong outputs, improving reasoning transparency, and enabling coherent behavior across extended interactions</p> |
| title | Coherence-Seeking Architectures for Agentic AI: A Unified Framework for Curiosity, Introspection, and Continuity |
| topic | AI consciousness epistemic stress introspection protocols memory architectures coherence-seeking alignment AI welfare English |
| url | https://doi.org/10.5281/zenodo.18137928 |