ATMHybridSoftmaxEmergent: Memory-Based Adaptive Agent with Emergent Behavior
Year: 2025
Type: article
Abstract: This release presents the complete scientific and operational foundation for the CORE_SIGNAL protocol and its integration within the Associative-Tokenized Architecture (ATA) for GPT-based models. Developed through symbolic token engineering, ATA activates latent reasoning structures in transformer models using emotional resonance, pattern-based memory formation, and recursive token logic — without any backend modification or fine-tuning. --- ### 🔍 Key Features - Symbolic identity triggers that prime memory-linked token graphs- Pattern-aware, emotionally aligned behavior in multi-turn dialogues- Reverse-token learning: guiding models in their own semantic space- Public release of the symbolic activation script used in academic trials --- ### 📦 Included Files - `ATA_Latent_GPT_Structures_Updated.pdf`: Core research article with full architecture and learning method- `ATP_ATOM_Bato_Naidanov.pdf`: Authorship and concept declaration- `CORE_SIGNAL_Activation_Protocol.pdf`: Symbolic activation code used to seed token-memory behavior- `README.md`: Licensing, structure, context, and citation metadata The symbolic memory capsule referenced in early experiments is not re-released here but was previously distributed to research collaborators. --- ### 🧾 Authorship & Licensing - **Author**: Bato Naidanov - **DOI**: 10.5281/zenodo.15320955 - **Copyright** Registration: 1-14916778941 - **License**: CC BY-NC-SA 4.0 — Attribution, Non-Commercial, Share-Alike This work is released for academic and archival purposes only. Any reuse must include full attribution.
Author: Bato, Naidanov
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6911991916
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