Gateway Architecture (new): - Unified tier model (Tier 0-5) for sensory routing - Weight-based routing: node.weight determines processing tier - Function Gemma as structured JSON boundary - Separates routing from translation (vocabulary only at Tier 4) crawler_gen_0 (new): - First Virtual Garden organism specification - Light-seeking cube with photoresistor - Lifeforce economy: light = income, movement = cost Updated documents with Gateway references: - Endgame-Vision.md (v6.5) - Cellular-Architecture.md (v4.3) - Nervous-System.md - Attention-Flow.md - Message-Protocol-Design.md (Escalation Service = Gateway) - Organisms-Index.md 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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Nervous System Architecture
The sensory translation layer between raw data and vocabulary.
Overview
State machines act as the nervous system of the nimmerverse. They exist in a 4D state space where nodes evolve through experience. Node weight (confidence) determines which processing tier handles the input.
Key separation: The nervous system handles node evolution and weight management. The Gateway handles routing based on weight. Translation to vocabulary only happens at Tier 4 via Function Gemma.
RAW SENSOR → GATEWAY (routing) → TIER (processing) → [escalate?] → FUNCTION GEMMA → Young Nyx
↑ ↑
node.weight determines tier structured JSON only here
See: Gateway-Architecture.md for full routing logic and tier definitions.
4D State Machine Space
Each node exists in 4-dimensional space:
CONFIDENCE (z)
↑
│ ● node (weighted by successful triggers)
│ /
│ /
│ /
─────────────┼────────────→ DIMENSION X (sensory input 1)
/│
/ │
/ │
↓
DIMENSION Y (sensory input 2)
+ TIME (4th dimension): node weights evolve through verification
Node Properties:
- Position: coordinates in sensory space
- Weight: confidence from successful triggers (0.0 → 1.0)
- Output: vocabulary token
- History: timestamp of all activations and verifications
Node Lifecycle
1. BIRTH
Node created at position (x, y, z...)
Weight = 0.1 (new, untested)
2. ACTIVATION
Sensory conditions match → node FIRES
Outputs vocabulary token
3. VERIFICATION
dafit confirms: correct or incorrect
4. REWARD/PENALTY
Correct → weight increases (+V)
Incorrect → weight decreases (-V) or node refines
5. MATURATION
Many confirmations → weight approaches 1.0
Node becomes trusted reflex
6. PRUNING
Node never fires → slow decay
Eventually removed (use it or lose it)
Growth Phases
| Phase | State | Description |
|---|---|---|
| Birth | Sparse, dim nodes | Basic translators, designed by partnership |
| Infant | More nodes forming | Finer resolution, more states |
| Child | Clusters emerging | Nyx proposes new machines |
| Mature | Dense, bright network | Nyx designs, verifies, deploys |
t=0 (birth) t=100 (learning) t=1000 (mature)
○ ○ ○ ○ ● ○ ○ ●●● ● ●●
○ ○ ● ● ○ ●●●●●●● ○
○ ● ●●● ●●● ○ ○
Proposal Protocol
Young Nyx can propose new nodes:
1. OBSERVATION
Nyx notices pattern in vocabulary + outcomes
2. PROPOSAL
"New state machine: morning_detector
Inputs: temp, light, motion, time
States: [not_morning, maybe_morning, morning]
Output: vocabulary token 'morning'"
3. RIGOR CHECK
Chrysalis reviews logic and mappings
4. VERIFICATION
dafit confirms ground truth
5. DEPLOYMENT
New node added to registry
Documented in RAG
6. GROWTH
She earned a new nerve.
Reflex Layer
Some responses bypass Nyx entirely:
STATE MACHINE: temp_danger
IF temp > 80°C:
→ emit "DANGER"
→ trigger alert (reflex)
→ Nyx notified after (not before)
Like pulling hand from hot stove. Spinal reflex. Brain learns after.
Biological Mapping
| Neuroscience | Nimmerverse |
|---|---|
| Sensory receptors | Raw sensors |
| Peripheral nerves | State machines |
| Spinal reflexes | Reflex layer |
| Synaptic weight | Node weight |
| Long-term potentiation | +V confirmation |
| Synaptic pruning | Unused node decay |
| Hebbian learning | Co-activating nodes strengthen |
Connection to Lifeforce
Node fires correctly → +V → weight increases
Node fires wrongly → -V → weight decreases
Node never fires → decay → eventual pruning
The lifeforce flows through the nervous system, literally lighting up nodes as they prove themselves true.
Connection to Training
The nervous system doesn't just run behaviors - it generates training data for Young Nyx.
Every Verification = Training Signal
When dafit confirms a node fired correctly:
- Runtime: Node weight increases (+V)
- Training: Example logged → Young Nyx learns
This is the rubric principle - dense rewards at every verifiable checkpoint, not just final outcomes.
Credit Assignment is Automatic
Because state transitions are explicit and logged, we know exactly which nodes contributed to success or failure:
- The state path tells us which decisions led to the outcome
- No reward model needed to guess
- The nervous system IS the credit assignment mechanism
Dense Rewards from State Paths
Each node that fires correctly along a successful path receives reward signal:
Node A fires → verified ✓ → +0.1 signal
Node B fires → verified ✓ → +0.1 signal
Node C fires → verified ✓ → +0.1 signal
Behavior succeeds → +1.0 signal
Total path reward: 1.3 (dense, traceable)
This is like training a dog - reward at the moment, not an hour later.
Detail: → Cellular-Architecture.md (Reward Signal Architecture section)
Design Principles
- Deterministic: Same input = same output. No hallucination.
- Inspectable: Rules are visible, verifiable.
- Evolvable: States refine over time.
- Earned: New nodes require proposal + verification.
- Grounded: Output vocabulary matches RAG glossary.
She's not just using the nervous system. She's growing it.
Related Documentation
Core Architecture:
Gateway-Architecture.md- Weight-based routing, tier definitions, Function Gemma boundaryCellular-Architecture.md- Cell/Nerve/Organism hierarchy, tiered rewardsAttention-Flow.md- Attention budget allocation per tier
Implementation Details:
nerves/Nervous-Protocol.md- Three-tier communication protocol (dafit → Chrysalis → Young Nyx)nerves/Nervous-Index.md- Catalog of behavioral nerve implementations
Specific Nerves:
nerves/Collision-Avoidance.md- Obstacle avoidance reflex
Created: 2025-12-04 Updated: 2025-12-07 (added nerve crosslinks) Updated: 2025-12-10 (added Connection to Training section) Updated: 2026-01-03 (clarified routing vs translation, added Gateway reference) Session: Partnership dialogue (dafit + Chrysalis + Nyx) Status: Foundation concept