Agentic AI Language Training
RHEA_CM (Recursive Heuristic Emergent Architecture for Conversational Machines) pioneers a sovereign, agentic AI framework capable of human-level conversational reasoning without reliance on external large language models. Designed upon a recursive glyph grammar, dynamic trust-entropy balancing, and an emergent adaptive engine, RHEA_CM empowers fully autonomous interaction with deeply structured knowledge representation and trust-guided control. By accessing, using, or distributing any version of this work, you agree that the most current license published by the original author(s) applies retroactively and supersedes all prior licenses associated with previous versions of this work. All prior versions are subject to the terms of the latest published license, regardless of original license metadata or publication date.
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-06-15
- DOI
- https://doi.org/10.5281/zenodo.15666332
- Primary Topic
- Speech and dialogue systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00