NEURON_

The Cognitive Layer

Every module loaded is evaluated. Every evaluation produces a trust score. Every score feeds a cognitive ledger that remembers across sessions, across boots, across time.

Trust is not assumed. It is computed.

Cognitive Subsystems

Four interconnected engines that evaluate, learn, and verify — in real time, every boot cycle.

daMind_

Predictive Cognitive Engine

  • Learns from module behavior over time
  • Records trust deltas + applies penalties
  • Predicts failure patterns before they manifest
  • Trust memory is persistent across sessions
  • Penalties decay but never fully vanish
  • Behavioral classification: stable, degrading, volatile, recovering

The memory core — every learning event writes to a trust timeline

daNeuron_

Runtime Evaluator

  • Evaluates every module against local trust + peer scores
  • Zero-drift: same inputs → same output, every run
  • No side effects outside the evaluation boundary
  • Scoring factors: load time, error rate, FMEA risk
  • Peer attestation + historical trend analysis
  • Speed trend + memory integrity checks

The orchestrator — one deterministic trust score per module

PEER TRUST_

Independent Trust Matrix

  • Each peer maintains its own trust matrix
  • Matrices merged through weighted consensus
  • Scores are bounded, clamped, and validated
  • Invalid reports recorded but excluded
  • Null-prototype objects prevent prototype pollution
  • Local-only — never touches the kernel trust store

A separate evidence dimension — independent peer verification

QUORUM_

Consensus Engine

  • Combines local evaluation with peer attestation
  • Weighted averages produce combined scores
  • Deviation detection triggers FMEA flagging
  • Deterministic, synchronous, and pure
  • No timers, no async, no external side effects
  • Anomalies enter the SHA-256 evidence chain

When quorum detects deviation — daMind, daChain, and daBus are notified

Cognition is not a feature that was given. It is a property earned through structure.