{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:6EKVWULUOC6VBCV75MCVZ4H5K2","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"c5f54dc989fd9df5b2efe329fb08b2618f89a9af77973787b2625894e332370f","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-03-24T12:50:48Z","title_canon_sha256":"e78aae9206280f4b006176e6b3e1a2b8fe94850b1b3f65ba77a959d57687bd2b"},"schema_version":"1.0","source":{"id":"2003.12151","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.12151","created_at":"2026-07-05T05:14:54Z"},{"alias_kind":"arxiv_version","alias_value":"2003.12151v3","created_at":"2026-07-05T05:14:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.12151","created_at":"2026-07-05T05:14:54Z"},{"alias_kind":"pith_short_12","alias_value":"6EKVWULUOC6V","created_at":"2026-07-05T05:14:54Z"},{"alias_kind":"pith_short_16","alias_value":"6EKVWULUOC6VBCV7","created_at":"2026-07-05T05:14:54Z"},{"alias_kind":"pith_short_8","alias_value":"6EKVWULU","created_at":"2026-07-05T05:14:54Z"}],"graph_snapshots":[{"event_id":"sha256:de6cdc2fd6c2b93979bcfb38d78475691d65c751893de45f2e266f75a651ae24","target":"graph","created_at":"2026-07-05T05:14:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2003.12151/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we introduce a regularized mean-field game and study learning of this game under an infinite-horizon discounted reward function. Regularization is introduced by adding a strongly concave regularization function to the one-stage reward function in the classical mean-field game model. We establish a value iteration based learning algorithm to this regularized mean-field game using fitted Q-learning. The regularization term in general makes reinforcement learning algorithm more robust to the system components. Moreover, it enables us to establish error analysis of the learning algo","authors_text":"Berkay Anahtarci, Can Deha Kariksiz, Naci Saldi","cross_cats":["cs.LG","cs.SY","eess.SY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-03-24T12:50:48Z","title":"Q-Learning in Regularized Mean-field Games"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.12151","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d43c8cb091fa0b697d57f631cbee77805f76924ff3450cb55f1e339fb93145be","target":"record","created_at":"2026-07-05T05:14:54Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"c5f54dc989fd9df5b2efe329fb08b2618f89a9af77973787b2625894e332370f","cross_cats_sorted":["cs.LG","cs.SY","eess.SY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2020-03-24T12:50:48Z","title_canon_sha256":"e78aae9206280f4b006176e6b3e1a2b8fe94850b1b3f65ba77a959d57687bd2b"},"schema_version":"1.0","source":{"id":"2003.12151","kind":"arxiv","version":3}},"canonical_sha256":"f1155b517470bd508abfeb055cf0fd568bc5cb30fe70c21d8cd23af2712b6d91","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f1155b517470bd508abfeb055cf0fd568bc5cb30fe70c21d8cd23af2712b6d91","first_computed_at":"2026-07-05T05:14:54.366087Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:14:54.366087Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"icwSQMNeBG+GZz8IeOBK+Dnf1j1LBaOm/EJMrkwiEm+cezAUUas1ke4/7dzR2TC7Dm3udiBGtY3iUnGBqU0qBg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:14:54.366625Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.12151","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d43c8cb091fa0b697d57f631cbee77805f76924ff3450cb55f1e339fb93145be","sha256:de6cdc2fd6c2b93979bcfb38d78475691d65c751893de45f2e266f75a651ae24"],"state_sha256":"03de7e92cf08c0ded54c3403f172a97db29f77a3d1f669cf49ace3b9972839be"}