Structural Life‑Regime Profiles#

• SLRP_module.json — Agentic module schema role assignments

A triadic substrate for cross‑domain life‑regime analysis

Structural Life‑Regime Profiles provide a unified, architecture‑agnostic framework for describing how biological and artificial systems perceive, process, and act within their environments. The goal is to align life‑regime modeling with the vST substrate, reduce conceptual drift, and simplify cross‑species and cross‑architecture comparisons.

This artifact introduces a minimal structural grammar for life‑regimes, enabling consistent classification across organisms, autonomous systems, and synthetic agents.

Purpose#

Life‑regimes emerge whenever a system maintains coherence through:

• structural constraints
• sensory coupling
• environmental interaction
• behavioral patterns
• drift and stability conditions

This project formalizes those regimes into a substrate‑level profile that can be applied to:

• biological species
• autonomous AI models
• robotics stacks
• synthetic lifeforms
• hybrid or emergent systems

The result is a cross‑domain atlas of life‑regimes that supports research, validation, and large‑scale comparative analysis.

Triadic Substrate#

Each life‑regime profile is organized around three structural layers:

1. Structural Regime#

Internal architecture, memory, learning capacity, computational constraints, and coherence mechanisms.

2. Sensory Regime#

Modalities, bandwidth, resolution, perceptual limits, and environmental coupling.

3. Environmental Regime#

Habitat, temporal cycles, social structure, resource patterns, and survival pressures.

These layers define the system’s “universe” — what it can sense, compute, predict, and respond to.

Regime Axes#

Life‑regime profiles are mapped using a set of invariant axes:

• structural complexity
• sensory modality profile
• environmental coupling
• behavioral regime (reflexive → tactical → strategic → symbolic)
• drift conditions
• stability anchors

These axes form a coordinate system for cross‑species and cross‑architecture comparison.

Applications#

Biological Systems#

Profiles reveal commonalities and differences across species, including:

• shared invariants
• regime disconnects
• sensory asymmetries
• environmental dependencies

Autonomous Systems#

Profiles simplify AI alignment and validation by requiring:

• declared sensory boundaries
• declared reasoning regimes
• declared failure postures
• drift‑aware transitions
• environment‑coupled behavior

This reduces architectural complexity and improves predictability.

Big‑Data Research#

The taxonomy supports large‑scale comparative datasets across:

• species
• agents
• robotics platforms
• synthetic lifeforms

Repository Structure#

docs/structural_life_regime_profiles/
├── README.md
├── substrate_definition.md
├── regime_axes.md
├── life_regime_taxonomy.md
├── cross_species_comparison.md
├── autonomous_system_alignment.md
├── drift_and_stability_profiles.md
├── glossary.md
└── references.md

Optional examples:

docs/structural_life_regime_profiles/examples/
├── human.md
├── chimpanzee.md
├── chrysina_gloriosa.md
├── llm_agent.md
├── robotics_stack.md
└── synthetic_lifeform.md

Status#

This artifact is part of the expanding TriadicFrameworks canon and serves as the bridge between biological life‑regimes and autonomous system regimes. It provides the structural foundation for future comparative studies, vST‑aligned modeling, and cross‑domain regime analysis.

Citation#

If you use this work, please cite the relevant TriadicFrameworks Zenodo entries. Each paper includes a CITATION.cff file with complete metadata.