coe-consensus

COE Consensus Engine — Cross-Model Consensus Skill for Shared World State Formation

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Install skill "coe-consensus" with this command: npx skills add schchit/coe-consensus

COE Consensus Skill

Cross-Model Consensus Engine

Algorithm implementation based on the COE (Cognition-Oriented Emergence) Protocol (Wang, 2026).

Core Problem

When multiple agents (humans, AI models, robots) observe the same physical space, how do they reach a verifiable consensus on "what the world is"?

Consensus Policies

PolicyUse CaseRule
Simple MajoritySmall equal-trust groupsConfirmations exceed 50% of all verifications received
Weighted TrustHeterogeneous agents with different reliabilitySum of (trust_weight * confidence) exceeds threshold
BFTHigh-security with potential malicious agentsMore than f+1 confirmations out of at least 2f+1 total verifications

Shared World State (SWS)

Whenever consensus is reached, the engine produces an SWS record containing:

  • subject / predicate / value — the agreed-upon fact
  • confidence — aggregated confidence score
  • based_on — event IDs of the underlying J/V events
  • consensus_policy — policy used to reach agreement
  • confirmations — number of confirming verifications

Usage Example

Request

{
  "session_id": "warehouse-001",
  "target": "warehouse-zone-3",
  "policy": "weighted_trust",
  "events": [
    {
      "event_id": "evt-1",
      "primitive": "J",
      "issuer": "robot-A",
      "timestamp": "2026-04-19T10:30:00Z",
      "target": "warehouse-zone-3",
      "assertion": {"subject": "door_01", "predicate": "status", "value": "open"},
      "confidence": 0.95
    },
    {
      "event_id": "evt-2",
      "primitive": "V",
      "issuer": "robot-B",
      "timestamp": "2026-04-19T10:30:05Z",
      "target": "warehouse-zone-3",
      "verify_of": ["evt-1"],
      "verification_result": "confirmed",
      "confidence": 0.9
    }
  ],
  "trust_weights": {"robot-A": 0.9, "robot-B": 0.8},
  "weighted_threshold": 1.5
}

Response

{
  "session_id": "warehouse-001",
  "resolved": true,
  "policy": "weighted_trust",
  "sws": {
    "sws_id": "...",
    "target": "warehouse-zone-3",
    "timestamp": "2026-04-19T10:30:05Z",
    "assertions": [
      {
        "subject": "door_01",
        "predicate": "status",
        "value": "open",
        "confidence": 1.0,
        "based_on": ["evt-1"],
        "consensus_policy": "weighted_trust",
        "confirmations": 1
      }
    ]
  },
  "conflicts": [],
  "message": "Consensus complete. 1 assertions resolved, 0 conflicts remain.",
  "events_processed": 2,
  "events_by_issuer": {"robot-A": 1, "robot-B": 1}
}

Relationship with JEP

  • COE answers "what the world is" — cognitive consensus, ex-ante / in-situ collaboration.
  • JEP answers "who is responsible" — accountability tracing, post-hoc audit.
  • COE events may be referenced by JEP as evidence. Together they form a complete cognition-accountability dual-loop.

Cognitive Emergence Lab
yuqiang@humanjudgment.org

Source Transparency

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