- name
- coe-consensus
- version
- 1.0.0
- description
- COE Consensus Engine — Cross-Model Consensus Skill for Shared World State Formation
- author
- Cognitive Emergence Lab <yuqiang@humanjudgment.org>
- license
- MIT
- protocol
- COE
- tags
- entrypoint
- skill.api:app
- host_targets
- skills
- description
- Collect J/V events from heterogeneous agents and produce a verifiable Shared World State via configurable consensus policy
- input_schema
- type
- object
- properties
- session_id
- type
- string
- description
- Unique session identifier
- target
- type
- string
- description
- Target world model or scene ID to filter events
- policy
- type
- string
- enum
- description
- Consensus policy to apply
- events
- type
- array
- description
- List of COE events (J, D, T, V primitives)
- items
- type
- object
- properties
- event_id
- type
- string
- primitive
- type
- string
- enum
- issuer
- type
- string
- timestamp
- type
- string
- target
- type
- string
- assertion
- type
- object
- verify_of
- type
- array
- items
- type
- string
- verification_result
- type
- string
- enum
- confidence
- type
- number
- terminate_of
- type
- string
- trust_weights
- type
- object
- description
- Issuer-to-weight mapping for weighted_trust policy
- bft_fault_tolerance
- type
- integer
- description
- Fault tolerance parameter f for BFT policy
- weighted_threshold
- type
- number
- description
- Confirmation threshold for weighted_trust policy
- required
- output_schema
- type
- object
- properties
- session_id
- type
- string
- resolved
- type
- boolean
- description
- Whether consensus was reached for all active assertions
- policy
- type
- string
- sws
- type
- object
- description
- Shared World State record when resolved
- properties
- sws_id
- type
- string
- target
- type
- string
- timestamp
- type
- string
- assertions
- type
- array
- items
- type
- object
- previous_sws_id
- type
- string
- conflicts
- type
- array
- description
- Unresolved conflicts requiring additional evidence or verifications
- items
- type
- object
- message
- type
- string
- events_processed
- type
- integer
- events_by_issuer
- type
- object
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
| Policy | Use Case | Rule |
|---|---|---|
| Simple Majority | Small equal-trust groups | Confirmations exceed 50% of all verifications received |
| Weighted Trust | Heterogeneous agents with different reliability | Sum of (trust_weight * confidence) exceeds threshold |
| BFT | High-security with potential malicious agents | More 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 factconfidence— aggregated confidence scorebased_on— event IDs of the underlying J/V eventsconsensus_policy— policy used to reach agreementconfirmations— 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