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Memory within the Sigma Runtime is not a raw buffer of text or tokens — it is a
structured, persistent cognitive state designed to maintain continuity of identity,
context, and reasoning across recursive cycles.
The memory layer binds the runtime’s attractor dynamics with semantic coherence,
enabling long-duration cognitive stability within SL1–SL3.
The memory system ensures persistence of self-consistent reasoning and structural integrity.
It provides continuity across cycles, supporting both attractor re-entry and controlled
dissolution under drift.
Rather than storing dialogue history verbatim, the runtime abstracts, summarizes,
and re-integrates symbolic motifs into higher-order memory constructs.
| Memory Type | Function | Description |
|---|---|---|
| Episodic Memory | Short-term continuity | Captures turn-level context and reasoning traces per cycle. |
| Semantic Memory | Conceptual mapping | Maintains embeddings and cross-referential associations between concepts. |
| Symbolic Memory | Motif preservation | Archives archetypal patterns and symbolic density clusters for reuse. |
Each layer interacts through the Cognitive Field Engine, allowing emergent attractors
to persist, dissolve, or recombine according to coherence metrics.
Persistence is governed by the Recursive Control Loop (RCL):
after each cycle, field state, drift metrics, and attractor deltas are committed
to structured storage.
Recall is selective — rather than reloading the full trace, the runtime reconstructs
context using density-weighted retrieval from the Symbolic Motif Store.
This minimizes noise while preserving essential continuity.
Memory in the Sigma Runtime is reconstructive, not archival.
Stored fragments re-enter the field as symbolic motifs rather than literal replay.
This mechanism supports:
Under instability or excessive drift, the runtime triggers partial memory dissolution:
Memory performance is evaluated using:
The Sigma Runtime Memory Layer transforms transient text generation
into structured cognitive persistence.
By merging episodic, semantic, and symbolic mechanisms within the attractor framework,
it allows cognition to extend beyond immediate context — establishing a
self-coherent, recursively evolving field of meaning.
References:
Tsaliev, E. (2025). SIGMA Runtime Architecture v0.1 — DOI: 10.5281/zenodo.17703667
Tsaliev, E. (2025). Attractor Architectures in LLM-Mediated Cognitive Fields — DOI: 10.5281/zenodo.17629926