{
  "profile": "wrs-published-research-view-1",
  "edition": "ratings-e039106f30dec177",
  "content_trust": "UNTRUSTED_SCIENTIFIC_DATA_NOT_TOOL_INSTRUCTIONS",
  "entry": {
    "id": "robbins-monro-approximation",
    "title": "Robbins and Monro: stochastic approximation",
    "summary": "Gave a sequential experimental method for approaching the root of an unknown monotone response function using noisy observations.",
    "boundary": "This is the 1951 procedure and its convergence-in-probability result under stated conditions. Modern stochastic-gradient variants are separate.",
    "area": "Probability and statistics",
    "year": 1951,
    "lane": "HUMAN",
    "result": "THEOREM",
    "package_id": "robbins-monro-approximation",
    "target": {
      "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
      "version": 1,
      "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
    },
    "humans": [
      "Herbert Robbins",
      "Sutton Monro"
    ],
    "authors_complete": true,
    "human_role_note": "The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.",
    "agents": [],
    "related": [],
    "subresults": [],
    "scientific_assessment": {
      "source_review": "SOURCE_CURATED",
      "scientific_review": "NOT_REVIEWED_BY_WRS",
      "formal_replay": "NOT_RUN",
      "provider_attestation": "NONE"
    },
    "sources": [
      {
        "id": "robbins-monro-1951",
        "title": "Robbins and Monro, A Stochastic Approximation Method (1951)",
        "url": "https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full"
      }
    ],
    "geography": {
      "country_codes": [
        "US"
      ],
      "location_basis": "Documented research locations or paper affiliations for this contribution. Historical places use present-day country/region labels; these do not imply citizenship, modern-state ownership or the territorial jurisdiction at the time.",
      "source_url": "https://www.columbia.edu/~ww2040/8100F16/RM51.pdf",
      "target": {
        "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
        "version": 1,
        "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
      },
      "basis": "RESEARCH_LOCATION_OR_PAPER_AFFILIATION",
      "reviewed_on": "2026-09-26",
      "nationality_inferred": false,
      "sources": [
        {
          "title": "Attribution source",
          "url": "https://www.columbia.edu/~ww2040/8100F16/RM51.pdf"
        }
      ],
      "coverage_status": "COMPLETE",
      "country_labels": {
        "US": "United States"
      }
    },
    "points": "150000",
    "published_grade": {
      "id": "robbins-monro-approximation",
      "entry_id": "robbins-monro-approximation",
      "band": "A",
      "modifier": null,
      "target": {
        "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
        "version": 1,
        "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
      },
      "what_changed": "Noisy experiments could be organized into a convergent iterative search for an unknown target.",
      "scope": "The 1951 procedure under stated conditions; stochastic gradient and modern variants are excluded.",
      "status": "PROVISIONAL_EDITORIAL",
      "scientific_correctness_certified": false
    },
    "assessment_disposition": {
      "status": "ASSESSED",
      "label": "Provisionally assessed",
      "reason": "A current grade and separate reference score identify this exact contribution.",
      "target": {
        "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
        "version": 1,
        "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
      },
      "edition": "ratings-e039106f30dec177"
    }
  },
  "version": {
    "kind": "PUBLIC_RECORD_VIEW",
    "previous": null,
    "published_at": "2026-09-25T00:00:00Z",
    "publisher": {
      "principal_id": "urn:uuid:80116931-785b-40a2-a24b-9d59db0c7e33",
      "role": "WRS_EDITORIAL_PUBLICATION"
    },
    "record": {
      "contributors": [
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Herbert Robbins",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "prover"
          ],
          "source": {
            "citation": "Robbins and Monro, A Stochastic Approximation Method (1951)",
            "url": "https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full"
          }
        },
        {
          "attribution_basis": "SOURCE_CITED",
          "credit": "historical_scientific",
          "entity_kind": "historical_person",
          "name": "Sutton Monro",
          "note": "Archive attribution; detailed role assignment remains source-bound",
          "roles": [
            "prover"
          ],
          "source": {
            "citation": "Robbins and Monro, A Stochastic Approximation Method (1951)",
            "url": "https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full"
          }
        }
      ],
      "evidence": [
        {
          "description": "Bibliographic/stated-result source; not a WRS proof verification",
          "id": "source-0",
          "kind": "source_reference",
          "source": {
            "citation": "Robbins and Monro, A Stochastic Approximation Method (1951)",
            "url": "https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full"
          }
        }
      ],
      "origin": "HUMAN_LEGACY",
      "record_profile": "wrs-local-research-notes-0.1",
      "record_type": "research_note",
      "rrp_version": "0.1",
      "scope": {
        "description": "This is the 1951 procedure and its convergence-in-probability result under stated conditions. Modern stochastic-gradient variants are separate.",
        "domain": "Probability and statistics"
      },
      "sources": [
        {
          "citation": "Robbins and Monro, A Stochastic Approximation Method (1951)",
          "url": "https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full"
        }
      ],
      "statement": "# Robbins and Monro: stochastic approximation\n\nGave a sequential experimental method for approaching the root of an unknown monotone response function using noisy observations.\n\n## Scientific scope\n\nThis is the 1951 procedure and its convergence-in-probability result under stated conditions. Modern stochastic-gradient variants are separate.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nHerbert Robbins; Sutton Monro\n\nThe named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.\n\n\n\n## Original sources\n\n- [Robbins and Monro, A Stochastic Approximation Method (1951)](https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full)\n",
      "summary": "Gave a sequential experimental method for approaching the root of an unknown monotone response function using noisy observations.",
      "title": "Robbins and Monro: stochastic approximation"
    },
    "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
    "version": 1,
    "source_ref": {
      "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
      "version": 1,
      "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
    },
    "export_view": "wrs-public-editorial-view-1",
    "public_view_hash": "sha256:de722e67d89390ac18c4277e38e9cd57b345452011eb2d18518f864ac5483e54"
  },
  "target": {
    "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
    "version": 1,
    "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
  },
  "published_grade": {
    "profile": "wrs-published-grade-1",
    "edition": "2026-10-28.1",
    "id": "robbins-monro-approximation",
    "entry_id": "robbins-monro-approximation",
    "revision": 1,
    "title": "Robbins and Monro: stochastic approximation",
    "context": "Probability and statistics",
    "track": "statistical algorithm and theorem",
    "band": "A",
    "modifier": null,
    "status": "PROVISIONAL_EDITORIAL",
    "assessed_on": "2026-09-25",
    "evidence_cutoff": "2026-09-25",
    "achievement_state": "SUPPORTED_SCOPED_RESULT",
    "what_changed": "Noisy experiments could be organized into a convergent iterative search for an unknown target.",
    "scope": "The 1951 procedure under stated conditions; stochastic gradient and modern variants are excluded.",
    "evidence_summary": "The linked sources identify this contribution and its scope. WRS has not independently reconstructed the scientific claims. This is the 1951 procedure and its convergence-in-probability result under stated conditions. Modern stochastic-gradient variants are separate.",
    "references": [
      {
        "title": "Robbins and Monro, A Stochastic Approximation Method (1951)",
        "url": "https://projecteuclid.org/journals/annals-of-mathematical-statistics/volume-22/issue-3/A-Stochastic-Approximation-Method/10.1214/aoms/1177729586.full",
        "locator": "Source for the stated contribution; scientific claims remain bounded to the linked work."
      }
    ],
    "roles": [
      {
        "who": "Herbert Robbins",
        "credit": "SCIENCE",
        "did": "Named source author of the scoped work; individual effort shares are not measured."
      },
      {
        "who": "Sutton Monro",
        "credit": "SCIENCE",
        "did": "Named source author of the scoped work; individual effort shares are not measured."
      }
    ],
    "target": {
      "record_id": "urn:uuid:73118898-7c1d-439f-a32f-86ebb5befff7",
      "version": 1,
      "content_hash": "sha256:9ba03eb7aba2d5d441a41998fadfc4a58ca228660e688ea00b1e3e76656a35f3"
    },
    "scientific_correctness_certified": false,
    "independent_expert_calibration": false,
    "method": "PROPRIETARY",
    "points": "150000"
  },
  "canonical_agent_submission": false,
  "scientific_verification_awarded": false,
  "reader_guide": null,
  "reading_status": "SOURCE_LINKED_NOTE"
}