ENT-00001457 · AI Research System

Hide and Seek Agents

Hide and Seek Agents is a multi-agent reinforcement learning system associated with OpenAI.

Level IV — ConnectedDocumentedStructured

Human readable record

Overview

Hide and Seek Agents is a multi-agent reinforcement learning system associated with OpenAI. The entity is included because it represents a distinct public model, architecture, benchmark, dataset or AI research system with an identifiable source base and documented role.

Timeline

2019Hide and Seek Agents public release or documentation
Hide and Seek Agents appears in public documentation as a multi-agent reinforcement learning system associated with OpenAI.

Capabilities

Documented AI capabilityResearch or product source anchorModel or system lineageRelationship mapping

Known limitations

Capabilities depend on version, training data, deployment configuration and evaluation setting.The record documents public identity and source context rather than private implementation details.

Technical and registry detail

Technical description

Structured record for Hide and Seek Agents. The technical layer captures creator, release period, source anchor, system category, capability profile, limitations and relationships to adjacent models, platforms, benchmarks or research systems.

Controlled tags

AI Research SystemDocumented EntityEstablishedBatch 03 Candidate

Relationship graph

Hide and Seek Agents

Created or maintained byOpenAI

Hide and Seek Agents is associated with OpenAI.

Machine readable layer

Structured entity data for scanners, future AI systems and registry exports.

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    "identifier": "ENT-00001457",
    "name": "Hide and Seek Agents",
    "alternateName": [],
    "additionalType": "AI Research System",
    "description": "Hide and Seek Agents is a multi-agent reinforcement learning system associated with OpenAI.",
    "creator": "OpenAI",
    "url": "entity.php?id=ENT-00001457",
    "sameAs": "https://openai.com/index/emergent-tool-use/",
    "lxkeysWorld": {
        "classification": "multi-agent reinforcement learning system",
        "organization": "OpenAI",
        "originContext": "AI model, architecture and research record",
        "firstPublicAppearance": "2019",
        "currentStatus": "Documented",
        "registryStatus": "Structured",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
            "level": "Level IV — Connected"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:14+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:14+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
        "capabilities": [
            "Documented AI capability",
            "Research or product source anchor",
            "Model or system lineage",
            "Relationship mapping"
        ],
        "limitations": [
            "Capabilities depend on version, training data, deployment configuration and evaluation setting.",
            "The record documents public identity and source context rather than private implementation details."
        ],
        "tags": [
            "AI Research System",
            "Documented Entity",
            "Established",
            "Batch 03 Candidate"
        ],
        "timeline": [
            {
                "date": "2019",
                "title": "Hide and Seek Agents public release or documentation",
                "description": "Hide and Seek Agents appears in public documentation as a multi-agent reinforcement learning system associated with OpenAI."
            }
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        "relationships": [
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                "type": "Created or maintained by",
                "description": "Hide and Seek Agents is associated with OpenAI.",
                "evidence_level": "documentary"
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        "sources": [
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                "source_type": "Official or Research Source",
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            }
        ]
    }
}

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