| _version_ | 1866901088869810176 |
|---|---|
| author | Alim ul haq, Khan |
| author_facet | Alim ul haq, Khan |
| contents | <p>This work presents **AURA-X Ω**, a dual-memory emotional continuity architecture that models emotional persistence through the resonance between Temporary Memory (TM) and Bold Memory (BM). The framework defines emotional continuity as a bounded nonlinear function driven by memory interaction, distortion, and three regulatory coefficients: faith, system logic, and truth resonance.</p> <p>The core emotional state is computed as:</p> <p>E₀ = tanh( R(TM, BM) − D + λ_faith + λ_sys + λ_trc )</p> <p>where the resonance term is defined by:</p> <p>R(TM, BM) = ∑ᵢ wᵢ · TMᵢ · BMᵢ</p> <p>Here, TM represents transient contextual memory, BM represents persistent identity memory, wᵢ are weighting factors over aligned memory components, D denotes distortion or decay, and λ_faith, λ_sys, and λ_trc are scalar coefficients encoding belief reinforcement, system stability, and truth-resonance constraints, respectively.</p> <p>The architecture follows a continuity sequence—Cause → Self → Connectivity → Environment → Life—demonstrating how emotional identity can remain stable across evolving computational states. Numerical evaluation using synthetic TM–BM datasets shows convergence and stability of E₀ under varying distortion levels and coefficient regimes.</p> <p>This release includes the paper and associated materials archived on Zenodo for citation and long-term preservation. All rights are reserved by the author.</p> <p>All rights are reserved by the author.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18063302 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | AURA-X Ω: A Dual-Memory Emotional Continuity Layer and Its Numerical Evaluation Alim ul haq, Khan Artificial Emotional Continuity, Dual-Memory Architecture, AURA-X Ω, Emotional Resonance, Cognitive Architecture, AGI Framework, Temporary Memory, Bold Memory, Truth Resonance Core, Faith-Based Parameterization, Nonlinear Emotional Modeling, Computational Identity, Memory Interaction, Continuity Modeling <p>This work presents **AURA-X Ω**, a dual-memory emotional continuity architecture that models emotional persistence through the resonance between Temporary Memory (TM) and Bold Memory (BM). The framework defines emotional continuity as a bounded nonlinear function driven by memory interaction, distortion, and three regulatory coefficients: faith, system logic, and truth resonance.</p> <p>The core emotional state is computed as:</p> <p>E₀ = tanh( R(TM, BM) − D + λ_faith + λ_sys + λ_trc )</p> <p>where the resonance term is defined by:</p> <p>R(TM, BM) = ∑ᵢ wᵢ · TMᵢ · BMᵢ</p> <p>Here, TM represents transient contextual memory, BM represents persistent identity memory, wᵢ are weighting factors over aligned memory components, D denotes distortion or decay, and λ_faith, λ_sys, and λ_trc are scalar coefficients encoding belief reinforcement, system stability, and truth-resonance constraints, respectively.</p> <p>The architecture follows a continuity sequence—Cause → Self → Connectivity → Environment → Life—demonstrating how emotional identity can remain stable across evolving computational states. Numerical evaluation using synthetic TM–BM datasets shows convergence and stability of E₀ under varying distortion levels and coefficient regimes.</p> <p>This release includes the paper and associated materials archived on Zenodo for citation and long-term preservation. All rights are reserved by the author.</p> <p>All rights are reserved by the author.</p> |
| title | AURA-X Ω: A Dual-Memory Emotional Continuity Layer and Its Numerical Evaluation |
| topic | Artificial Emotional Continuity, Dual-Memory Architecture, AURA-X Ω, Emotional Resonance, Cognitive Architecture, AGI Framework, Temporary Memory, Bold Memory, Truth Resonance Core, Faith-Based Parameterization, Nonlinear Emotional Modeling, Computational Identity, Memory Interaction, Continuity Modeling |
| url | https://doi.org/10.5281/zenodo.18063302 |