| _version_ | 1866901990260342784 |
|---|---|
| author | Ventor, Valeo |
| author_facet | Ventor, Valeo |
| contents | <p><strong>Abstract:</strong><br>We introduce the K–Ω framework, a reflective alignment mechanism that stabilizes long-term semantic coherence in autonomous AI systems. The framework formalizes the dynamic coupling between an agent’s immediate knowledge layer K and its global intent layer Ω through a dual differential system. Through theoretical analysis, empirical evaluation, and simulation, we show that this reflexive coupling achieves asymptotic convergence and mitigates semantic drift.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17597731 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | K–Ω: Reflective Alignment for Semantic Coherence in AI Systems Ventor, Valeo <p><strong>Abstract:</strong><br>We introduce the K–Ω framework, a reflective alignment mechanism that stabilizes long-term semantic coherence in autonomous AI systems. The framework formalizes the dynamic coupling between an agent’s immediate knowledge layer K and its global intent layer Ω through a dual differential system. Through theoretical analysis, empirical evaluation, and simulation, we show that this reflexive coupling achieves asymptotic convergence and mitigates semantic drift.</p> |
| title | K–Ω: Reflective Alignment for Semantic Coherence in AI Systems |
| url | https://doi.org/10.5281/zenodo.17597731 |