{
  "id": "rl_engine",
  "label": "RL Engine Canonical",
  "phase": "phase-08",
  "category": "memory_learning_reasoning",
  "status": "ACTIVE_DH_MIRROR",
  "purpose": "Define how reinforcement-style learning is represented, constrained and evaluated before it can influence DEVON-DEV behavior.",
  "function": "Improve prioritization, recovery suggestion, context selection, risk prediction, error classification, patch quality and append-abuse detection without gaining authority to change canon, approve production, bypass FSM or execute dangerous commands.",
  "technology_requirements": [
    {
      "technology": "RL Engine Service",
      "required_for": "Define how reinforcement-style learning is represented, constrained and evaluated before it can influence DEVON-DEV behavior.",
      "required_by_phase": "phase-08",
      "required_by_category": "rl_engine",
      "required_by_buckets": [
        "Prerequisites",
        "Installation",
        "Configuration",
        "Validation",
        "Observable Evidence",
        "Failure Modes & Recovery",
        "Completion & Promotion"
      ],
      "expected_version": "MISSING until implemented and validated in the future Execution & Monitoring Panel",
      "validation_command": "MISSING until rl_engine can prove source, scope, state, evidence and decision linkage",
      "evidence_path": "/home/yeff/public_html/devon/canon/execution/state/dh_sources/rl_engine_canonical.json",
      "status_source": "Documentation Hub + future Execution & Monitoring Panel",
      "blocking_if_missing": true,
      "failure_impact": "MISSING applies when adaptive scoring has no source, scope or governance boundary. FAIL applies when optimization begins to override policy, reward speed over safety, promote unapproved behavior or treat repeated success as authority. Without this category, DEVON-DEV loses adaptive improvement; with it uncontrolled, DEVON-DEV drifts."
    }
  ],
  "depends_on": [
    "learning_gov",
    "memory_lifecycle",
    "knowledge_versioning",
    "execution_ledger",
    "observable_evidence",
    "fsm_absolute_decision"
  ],
  "used_by": [
    "future_execution_monitoring_panel",
    "planning_reasoning",
    "tool_execution",
    "learning_gov"
  ]
}