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Core Ideas

Nyreth is a symbolic cognitive engine based on:

- Recursive symbolic reasoning
- Tensor-based multidimensional glyph encoding
- Resonance field dynamics for meaning evolution
- Dynamic symbolic morphogenesis (glyph generation and evolution)
- Symbolic gateway security architecture

Version 1 Demo Release - Primary Modules


- Glyph Library: Core dataset of glyphs with tensor encoding and metadata
- Recursive Engine: Traverses glyph pathways recursively based on resonance and context
- Symbolic Memory Network: Stores traces, strengthens connections, generates emergent pathways
- Insight Synthesizer: Analyses symbolic traces to compress and generate higher-order meaning
- Traversal Engine: Controls dynamic symbolic traversal; supports both headless and GUI modes
- Interpretive Compression: Reconstructs symbolic traces into compressed, human-interpretable insights
- Semantic Reasoning Overlay: Naturalises symbolic insights for interface with human queries or LLMs
- GUI: Visualises glyphs, resonance fields, recursive traces, and morphogenesis
- PseudoLLM: a demo proxy to simulate a LLM model interfacing with Nyreth for referring queries

Data Structures


- Glyph Object: Contains metadata such as glyph name, translation, category, and tensor values
- Tensor Arrays: Numerical vectors encoding glyph cognitive dimensions
- Trace Records: Sequences of glyphs traversed during recursion, stored with resonance metrics
- Morph Datasets: Morphogenic transitions of tensor values across symbolic evolution events

Cognitive Mechanics


- Recursive Reasoning: Progresses symbolically through glyph pathways, adapting dynamically
- Resonance Modulation: Glyphs strengthen or weaken based on symbolic relevance over time
- Morphogenesis: New glyphs can be synthesised where new meaning can be formed from combining existing glyphs
- Pruning: The aim is not unrestricted generation of glyphs but a focus on important and useful ones,
so a pruning function allows unneeded, surplus composite glyphs to be removed.



Nyreth's recursive aspect lies in its traversal engine, which re-enters and re-evaluates glyphs based on semantic resonance, structural roles and prior trace influence. Although the trace overlay output appears linear, the logic beneath it involves cyclic glyph reinforcement and repetition of salient motifs, which creates a recursive refinement of understanding before the final path becomes apparent.