Gorde:
| Egile nagusia: | |
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| Formatua: | Recurso digital |
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| Argitaratua: |
Zenodo
2026
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| Sarrera elektronikoa: | https://doi.org/10.5281/zenodo.20257302 |
| Etiketak: |
Etiketa erantsi
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Aurkibidea:
- <div><strong>UAU–META / NSCF–Ω (v5.6-CONVERGED)</strong></div> <div><strong>SELF-CONSISTENT STOCHASTIC OPERATOR GEOMETRY</strong></div> <div><strong>WITH RECURSIVE PHASE DYNAMICS, AUTOLOGICAL CLOSURE AND ACTIVE INFERENCE DECOMPOSITION</strong></div> <div><strong>Formal Integrated Specification v5.6</strong></div> <div><strong>Research-Level Mathematical Architecture — Full Convergence Block</strong></div> <div>================================================================================<br> <div> </div> <div>Vitaly Bazarov</div> <div>ORCID: <a href="https://orcid.org/0009-0007-9967-5807" rel="noopener">https://orcid.org/0009-0007-9967-5807</a></div> <div> </div> <div>STATUS</div> <div>--------------------------------------------------------------------------------</div> <div>Fully Converged Peer-Review Mathematical Framework</div> <div> </div> <div>================================================================================</div> <div>0. GLOBAL SEMANTIC INTERPRETATION</div> <div>================================================================================</div> <div>The framework defines and closes a class of self-consistent stochastic operator </div> <div>systems on Wasserstein probability spaces characterized by:</div> <div> • adaptive measure dynamics</div> <div> • nonlinear operator feedback</div> <div> • entropy-regulated evolution</div> <div> • delayed stochastic adaptive bifurcation</div> <div> • spectral phase transitions</div> <div> • recursive categorical evolution</div> <div> • noise-to-structure conversion</div> <div> • autological adaptation of laws</div> <div> </div> <div>The system EXCLUDES anthropomorphic metaphors (such as consciousness, free will, </div> <div>or ungrounded AGI claims) and is strictly interpreted as an open, non-linear </div> <div>dissipative structure executing adaptive geometric regulation of its internal </div> <div>geometry under the pressure of external uncertainty (Cosmological Microwave </div> <div>Background / CMB background noise).</div> <p>This record is a version of the Univers Logos — UAU project. <br>It contains an early description of the mathematical formulation of the Universal Attention Unit (UAU): </p> <div>Base model : <strong>UAU = (η × N_free) / T</strong></div> <div> </div> <div>where:</div> <div> </div> <div>η (eta): efficiency or transformation coefficient,</div> <div>N_free: number of free or available units (resources, energy, or attention),</div> <div>T: time, representing the temporal dimension of cognition and action.</div> <div> </div> <div> </div> <div> </div> <div>η (eta) is the dimensionless energy–information efficiency coefficient (η_EI) in the UAU model. It quantifies the fraction of available resources that is effectively transformed into useful ordered output, ranging from 0 (complete dissipation) to 1 (ideal, lossless conversion). η incorporates thermodynamic constraints such as the Landauer limit and functions as a quality multiplier that converts raw resource quantity into meaningful efficiency within the base formula UAU = (η × N_free) / T.</div> <div> </div> <div>N_free represents the quantity of free or available resources in the UAU model. This includes energy, computational capacity, attention quanta, memory, or other system resources accessible at time t for transformation into ordered output. In the base formula UAU = (η × N_free) / T, N_free serves as the scalable resource term directly modulated by the efficiency coefficient η.</div> <div> </div> <div>T is the effective integration time window in the UAU model. It defines the temporal scale over which available resources are transformed into ordered output (typically 0.2–0.5 seconds for cognitive and attentional processes). In the base formula UAU = (η × N_free) / T, T functions as the normalizing temporal divisor determining the rate of transformation.</div> <p>Bazarov, V. (2025). Model UAU Universal Attention Unit. Zenodo.<br><br>https://doi.org/10.5281/zenodo.17033793</p> https://doi.org/10.5281/zenodo.17034024</div>