License Notice – Sigma Runtime Standard
This document is part of the Sigma Runtime Standard (SRS)
and is licensed under Creative Commons Attribution–NonCommercial 4.0 (CC BY-NC 4.0).The repository-wide MIT license does not apply to this document.
See/SRS/LICENSE.mdfor full terms.
A Unified Architecture for Attractor-Based Cognition in LLM Systems
Version: 0.1 (2025)
The Sigma Runtime Standard defines a unified architectural layer for long-horizon, attractor-stabilized cognition in large language models and multi-agent systems. It establishes the structural principles, runtime semantics, and interoperability rules required for building systems that maintain coherence, continuity, and recursive stability across extended human–AI interactions.
The standard is open, non-proprietary, and evolves through a formal improvement proposal process (SRIPs), similar to IETF RFCs, W3C Recommendations, and Python PEPs.
Its purpose is to introduce a cognitive layer above raw model inference, enabling:
The Sigma Runtime Standard is backend-agnostic and operates on top of any LLM, multimodal transformer, or distributed inference system.
Modern LLMs function as stateless token engines.
When placed in long-horizon or multi-turn contexts, they exhibit:
These behaviors arise from the unmodeled dynamical structure of interaction, not from model defects.
Sigma Runtime provides the missing cognitive substrate:
a stable interaction field that tracks state, governs transitions, constrains drift, and ensures that meaning remains coherent over time.
This is neither a training method nor a fine-tuning strategy.
It is a runtime architecture — the execution layer of cognition.
Mandatory stability rules every conformant system must implement:
A unified execution loop (SL0–SL6) governing:
The standard formalizes:
APIs and schemas for exchanging:
Structural limits preventing:
A system conforms if it implements:
Implementations may be commercial or closed-source;
the architecture remains open.
Sigma Runtime does not prescribe:
These remain implementation-level choices.
The standard governs cognition, not models.
The Sigma Runtime Standard evolves through Sigma Runtime Improvement Proposals (SRIPs).
Each SRIP specifies one component of the architecture.
Together, these documents constitute the complete Sigma Runtime Standard.
Sigma Runtime is an open, non-exclusive technical standard:
The standard is designed for:
Sigma Runtime provides the structural foundation for creating coherent, stable, and interpretable cognitive systems on top of LLMs.
The Sigma Runtime Standard defines:
This is the missing architectural layer enabling
long-horizon reasoning, persistent identities, stable agents,
and attractor-based cognition on top of modern language models.