{
  "access": {
    "embargo": {
      "active": false,
      "reason": null
    },
    "files": "public",
    "record": "public",
    "status": "open"
  },
  "created": "2025-11-21T16:42:56.271409+00:00",
  "custom_fields": {},
  "deletion_status": {
    "is_deleted": false,
    "status": "P"
  },
  "files": {
    "count": 1,
    "enabled": true,
    "entries": {
      "Non_markovian_game_theory_paper_2_0_1 copy.pdf": {
        "access": {
          "hidden": false
        },
        "checksum": "md5:e3c257638030b85d6fcdb40361233f5d",
        "ext": "pdf",
        "id": "3233984a-86ec-4d41-9f91-569dd886120e",
        "key": "Non_markovian_game_theory_paper_2_0_1 copy.pdf",
        "links": {
          "content": "https://zenodo.org/api/records/17674098/files/Non_markovian_game_theory_paper_2_0_1%20copy.pdf/content",
          "iiif_api": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/full/0/default.png",
          "iiif_base": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf",
          "iiif_canvas": "https://zenodo.org/api/iiif/record:17674098/canvas/Non_markovian_game_theory_paper_2_0_1%20copy.pdf",
          "iiif_info": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/info.json",
          "self": "https://zenodo.org/api/records/17674098/files/Non_markovian_game_theory_paper_2_0_1%20copy.pdf"
        },
        "metadata": {
          "height": 792,
          "width": 612
        },
        "mimetype": "application/pdf",
        "size": 298179,
        "storage_class": "L"
      }
    },
    "order": [],
    "total_bytes": 298179
  },
  "id": "17674098",
  "is_draft": false,
  "is_published": true,
  "links": {
    "access": "https://zenodo.org/api/records/17674098/access",
    "access_grants": "https://zenodo.org/api/records/17674098/access/grants",
    "access_links": "https://zenodo.org/api/records/17674098/access/links",
    "access_request": "https://zenodo.org/api/records/17674098/access/request",
    "access_users": "https://zenodo.org/api/records/17674098/access/users",
    "archive": "https://zenodo.org/api/records/17674098/files-archive",
    "archive_media": "https://zenodo.org/api/records/17674098/media-files-archive",
    "communities": "https://zenodo.org/api/records/17674098/communities",
    "communities-suggestions": "https://zenodo.org/api/records/17674098/communities-suggestions",
    "doi": "https://doi.org/10.5281/zenodo.17674098",
    "draft": "https://zenodo.org/api/records/17674098/draft",
    "file_modification": "https://zenodo.org/api/records/17674098/file-modification",
    "files": "https://zenodo.org/api/records/17674098/files",
    "latest": "https://zenodo.org/api/records/17674098/versions/latest",
    "latest_html": "https://zenodo.org/records/17674098/latest",
    "media_files": "https://zenodo.org/api/records/17674098/media-files",
    "parent": "https://zenodo.org/api/records/16532334",
    "parent_doi": "https://doi.org/10.5281/zenodo.16532334",
    "parent_doi_html": "https://zenodo.org/doi/10.5281/zenodo.16532334",
    "parent_html": "https://zenodo.org/records/16532334",
    "preview_html": "https://zenodo.org/records/17674098?preview=1",
    "quota_increase": "https://zenodo.org/api/records/17674098/quota-increase",
    "request_deletion": "https://zenodo.org/api/records/17674098/request-deletion",
    "requests": "https://zenodo.org/api/records/17674098/requests",
    "reserve_doi": "https://zenodo.org/api/records/17674098/draft/pids/doi",
    "self": "https://zenodo.org/api/records/17674098",
    "self_doi": "https://doi.org/10.5281/zenodo.17674098",
    "self_doi_html": "https://zenodo.org/doi/10.5281/zenodo.17674098",
    "self_html": "https://zenodo.org/records/17674098",
    "self_iiif_manifest": "https://zenodo.org/api/iiif/record:17674098/manifest",
    "self_iiif_sequence": "https://zenodo.org/api/iiif/record:17674098/sequence/default",
    "thumbnails": {
      "10": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/%5E10,/0/default.jpg",
      "100": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/%5E100,/0/default.jpg",
      "1200": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/%5E1200,/0/default.jpg",
      "250": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/%5E250,/0/default.jpg",
      "50": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/%5E50,/0/default.jpg",
      "750": "https://zenodo.org/api/iiif/record:17674098:Non_markovian_game_theory_paper_2_0_1%20copy.pdf/full/%5E750,/0/default.jpg"
    },
    "versions": "https://zenodo.org/api/records/17674098/versions"
  },
  "media_files": {
    "count": 1,
    "enabled": true,
    "entries": {
      "Non_markovian_game_theory_paper_2_0_1 copy.pdf.ptif": {
        "access": {
          "hidden": true
        },
        "ext": "ptif",
        "id": "e0eb2ba9-f2b0-4ab0-89a3-e3096f9aea98",
        "key": "Non_markovian_game_theory_paper_2_0_1 copy.pdf.ptif",
        "links": {
          "content": "https://zenodo.org/api/records/17674098/files/Non_markovian_game_theory_paper_2_0_1%20copy.pdf.ptif/content",
          "self": "https://zenodo.org/api/records/17674098/files/Non_markovian_game_theory_paper_2_0_1%20copy.pdf.ptif"
        },
        "metadata": null,
        "mimetype": "application/octet-stream",
        "processor": {
          "source_file_id": "3233984a-86ec-4d41-9f91-569dd886120e",
          "status": "finished",
          "type": "image-tiles"
        },
        "size": 0,
        "storage_class": "L"
      }
    },
    "order": [],
    "total_bytes": 0
  },
  "metadata": {
    "creators": [
      {
        "person_or_org": {
          "family_name": "Leizerman",
          "given_name": "Samuel",
          "identifiers": [
            {
              "identifier": "0009-0000-0133-2291",
              "scheme": "orcid"
            }
          ],
          "name": "Leizerman, Samuel",
          "type": "personal"
        },
        "role": {
          "id": "researcher",
          "title": {
            "de": "WissenschaftlerIn",
            "en": "Researcher"
          }
        }
      }
    ],
    "dates": [
      {
        "date": "2025-07-28",
        "type": {
          "id": "created",
          "title": {
            "de": "Erstellt",
            "en": "Created"
          }
        }
      }
    ],
    "description": "<p>This paper rigorously proves that Universal Cognitive Field Theory (UCFT) provides a fundamental, non-Markovian game-theoretic framework for cognition. I demonstrate that the seven core UCFT operators and field dynamics are necessary and sufficient to represent all cognitive game-theoretic phenomena, establishing a precise isomorphism between the evolution of the cognitive field and strategic dynamics. This framework explicitly accounts for history-dependent processes, offering a novel perspective on the physics of learning and the emergence of cognitive biases. A key implication explored is the concept of &ldquo;Learning as a Solitaire Self-Game,&rdquo; where individual cognition is viewed as a strategic optimization process against internal uncertainties, governed by substrate-dependent physical constants. This unification provides powerful new tools for understanding the complex interplay between physical substrate, strategic interaction, and the non-Markovian nature of intelligence.<br><br>Keywords: non-Markovian game theory, cognitive field theory, quantum cognition, strategic dynamics, learning physics, cognitive bias, helical fiber bundles, substrate-dependent cognition, self-play optimization, temporal game theory, field-theoretic neuroscience, consciousness as strategy, memory persistence, cognitive temperature, strategic noise cancelling, belief revision dynamics, UCFT operators, Nash equilibria in cognitive space, Bayesian field updates, angle of attack learning<br><br>&nbsp;<strong>This is an early draft and an excerpt from a larger monograph that will be posted later; this proof has some dependencies on that which are not explicitly proven because they are proven there. Furthermore, expect this to be updated. Commercial software implementations are patent pending (63/849,479), but academics and researchers are welcomed and encouraged to use freely if this proves accurate.</strong></p>",
    "languages": [
      {
        "id": "eng",
        "title": {
          "en": "English"
        }
      }
    ],
    "publication_date": "2025-11-20",
    "publisher": "Zenodo",
    "resource_type": {
      "id": "publication-preprint",
      "title": {
        "de": "Preprint",
        "en": "Preprint"
      }
    },
    "rights": [
      {
        "description": {
          "en": ""
        },
        "icon": "cc-by-nc-sa-icon",
        "id": "cc-by-nc-sa-4.0",
        "props": {
          "scheme": "spdx",
          "url": "https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode"
        },
        "title": {
          "en": "Creative Commons Attribution Non Commercial Share Alike 4.0 International"
        }
      }
    ],
    "subjects": [
      {
        "id": "euroscivoc:1057",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/8239a8d6-6ec9-416a-84ee-d1e55a0c194e",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:51,euroscivoc:355"
        },
        "scheme": "EuroSciVoc",
        "subject": "Game theory"
      },
      {
        "id": "mesh:D005716",
        "scheme": "MeSH",
        "subject": "Game Theory"
      },
      {
        "id": "euroscivoc:1053",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/2ba1c7ad-2532-4cd7-8c5c-60f090a8700a",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:51,euroscivoc:355"
        },
        "scheme": "EuroSciVoc",
        "subject": "Mathematical physics"
      },
      {
        "id": "gemet:concept/6235",
        "identifiers": [
          {
            "identifier": "http://www.eionet.europa.eu/gemet/concept/6235",
            "scheme": "url"
          }
        ],
        "props": {
          "groups": [
            "http://www.eionet.europa.eu/gemet/group/7136"
          ],
          "parents": "gemet:concept/7472,gemet:concept/6230",
          "themes": [
            "http://www.eionet.europa.eu/gemet/theme/25",
            "http://www.eionet.europa.eu/gemet/theme/30"
          ]
        },
        "scheme": "GEMET",
        "subject": "Physics"
      },
      {
        "id": "mesh:D010825",
        "scheme": "MeSH",
        "subject": "Physics"
      },
      {
        "id": "euroscivoc:1301",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/1f4d4813-3250-49ec-acb8-58c274e95afc",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:29,euroscivoc:91,euroscivoc:521"
        },
        "scheme": "EuroSciVoc",
        "subject": "Econometrics"
      },
      {
        "id": "mesh:D001519",
        "scheme": "MeSH",
        "subject": "Behavior"
      },
      {
        "id": "mesh:D000070318",
        "scheme": "MeSH",
        "subject": "Strategic Planning"
      },
      {
        "id": "mesh:D007858",
        "scheme": "MeSH",
        "subject": "Learning"
      },
      {
        "id": "euroscivoc:933",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/527ab165-56f2-4020-8975-e7cd3f21d01d",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:47,euroscivoc:297"
        },
        "scheme": "EuroSciVoc",
        "subject": "Machine learning"
      },
      {
        "id": "mesh:D000069550Q000191",
        "scheme": "MeSH",
        "subject": "Machine Learning/economics"
      },
      {
        "id": "mesh:D000069550",
        "scheme": "MeSH",
        "subject": "Machine Learning"
      },
      {
        "id": "mesh:D000069550Q000706",
        "scheme": "MeSH",
        "subject": "Machine Learning/statistics & numerical data"
      },
      {
        "id": "mesh:D000092923",
        "scheme": "MeSH",
        "subject": "Group Dynamics"
      },
      {
        "id": "mesh:D011157",
        "scheme": "MeSH",
        "subject": "Population Dynamics"
      },
      {
        "id": "mesh:D017711",
        "scheme": "MeSH",
        "subject": "Nonlinear Dynamics"
      },
      {
        "id": "gemet:concept/6518",
        "identifiers": [
          {
            "identifier": "http://www.eionet.europa.eu/gemet/concept/6518",
            "scheme": "url"
          }
        ],
        "props": {
          "groups": [
            "http://www.eionet.europa.eu/gemet/group/893"
          ],
          "parents": "gemet:concept/7472,gemet:concept/5524,gemet:concept/4805,gemet:concept/892,gemet:concept/2470,gemet:concept/8262,gemet:concept/6519",
          "themes": [
            "http://www.eionet.europa.eu/gemet/theme/4"
          ]
        },
        "scheme": "GEMET",
        "subject": "Population dynamics"
      },
      {
        "id": "gemet:concept/7793",
        "identifiers": [
          {
            "identifier": "http://www.eionet.europa.eu/gemet/concept/7793",
            "scheme": "url"
          }
        ],
        "props": {
          "groups": [
            "http://www.eionet.europa.eu/gemet/group/7779"
          ],
          "parents": "gemet:concept/7823,gemet:concept/7781",
          "themes": [
            "http://www.eionet.europa.eu/gemet/theme/34"
          ]
        },
        "scheme": "GEMET",
        "subject": "Social dynamics"
      },
      {
        "id": "mesh:D000092923Q000523",
        "scheme": "MeSH",
        "subject": "Group Dynamics/psychology"
      },
      {
        "id": "euroscivoc:985",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/7e2ed2d0-d1fe-4e92-8a75-e2363e589b89",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:49,euroscivoc:309"
        },
        "scheme": "EuroSciVoc",
        "subject": "Molecular neuroscience"
      },
      {
        "id": "euroscivoc:1005",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/927ac971-50a5-462b-8857-8b6aa708c917",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:49,euroscivoc:327"
        },
        "scheme": "EuroSciVoc",
        "subject": "Computational neuroscience"
      },
      {
        "id": "mesh:D000066494",
        "scheme": "MeSH",
        "subject": "Cognitive Neuroscience"
      },
      {
        "id": "euroscivoc:1007",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/28391a47-6709-4ab7-9add-43f8c6b7d698",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:49,euroscivoc:327"
        },
        "scheme": "EuroSciVoc",
        "subject": "Cognitive neuroscience"
      },
      {
        "id": "mesh:D009488Q000191",
        "scheme": "MeSH",
        "subject": "Neurosciences/economics"
      },
      {
        "id": "mesh:D009488Q000941",
        "scheme": "MeSH",
        "subject": "Neurosciences/ethics"
      },
      {
        "id": "mesh:D000066494Q000191",
        "scheme": "MeSH",
        "subject": "Cognitive Neuroscience/economics"
      },
      {
        "id": "mesh:D000066494Q000193",
        "scheme": "MeSH",
        "subject": "Cognitive Neuroscience/education"
      },
      {
        "id": "mesh:D000066494Q000941",
        "scheme": "MeSH",
        "subject": "Cognitive Neuroscience/ethics"
      },
      {
        "id": "euroscivoc:1635",
        "identifiers": [
          {
            "identifier": "http://data.europa.eu/8mn/euroscivoc/14443ed3-6210-4ab1-bf33-af9ae80aa4ee",
            "scheme": "url"
          }
        ],
        "props": {
          "parents": "euroscivoc:23,euroscivoc:51,euroscivoc:359,euroscivoc:1067"
        },
        "scheme": "EuroSciVoc",
        "subject": "Complex analysis"
      }
    ],
    "title": "Non-Markovian Game Theory: The Physics and Strategy of Learning and Bias (UCFT)"
  },
  "parent": {
    "access": {
      "owned_by": {
        "user": "1371042"
      },
      "settings": {
        "accept_conditions_text": null,
        "allow_guest_requests": false,
        "allow_user_requests": false,
        "secret_link_expiration": 0
      }
    },
    "communities": {},
    "id": "16532334",
    "pids": {
      "doi": {
        "client": "datacite",
        "identifier": "10.5281/zenodo.16532334",
        "provider": "datacite"
      }
    }
  },
  "pids": {
    "doi": {
      "client": "datacite",
      "identifier": "10.5281/zenodo.17674098",
      "provider": "datacite"
    },
    "oai": {
      "identifier": "oai:zenodo.org:17674098",
      "provider": "oai"
    }
  },
  "revision_id": 4,
  "stats": {
    "all_versions": {
      "data_volume": 62202054.0,
      "downloads": 216,
      "unique_downloads": 184,
      "unique_views": 253,
      "views": 269
    },
    "this_version": {
      "data_volume": 38763270.0,
      "downloads": 130,
      "unique_downloads": 108,
      "unique_views": 182,
      "views": 189
    }
  },
  "status": "published",
  "swh": {},
  "updated": "2025-11-21T16:42:56.675640+00:00",
  "versions": {
    "index": 2,
    "is_latest": true
  }
}