{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:KBJQK55SJKN4ZCXO63WO7UU547","short_pith_number":"pith:KBJQK55S","canonical_record":{"source":{"id":"2008.10870","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-25T07:59:20Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"db82fbf5469a91f12a3ab9fb870821c8907808389739d58a1adeef89039065dd","abstract_canon_sha256":"ae4f5ba6600c233553d5ecf788cf50835e6f58f8517ea8b1528d461ce56672d5"},"schema_version":"1.0"},"canonical_sha256":"50530577b24a9bcc8aeef6ecefd29de7da31bb2191f911a0c0aa383a251eb8f7","source":{"kind":"arxiv","id":"2008.10870","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.10870","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"arxiv_version","alias_value":"2008.10870v2","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.10870","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"pith_short_12","alias_value":"KBJQK55SJKN4","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"pith_short_16","alias_value":"KBJQK55SJKN4ZCXO","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"pith_short_8","alias_value":"KBJQK55S","created_at":"2026-07-05T02:30:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:KBJQK55SJKN4ZCXO63WO7UU547","target":"record","payload":{"canonical_record":{"source":{"id":"2008.10870","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-25T07:59:20Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"db82fbf5469a91f12a3ab9fb870821c8907808389739d58a1adeef89039065dd","abstract_canon_sha256":"ae4f5ba6600c233553d5ecf788cf50835e6f58f8517ea8b1528d461ce56672d5"},"schema_version":"1.0"},"canonical_sha256":"50530577b24a9bcc8aeef6ecefd29de7da31bb2191f911a0c0aa383a251eb8f7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:30:59.322894Z","signature_b64":"S2oCk5/zInQjqnBWG1P5fPzZ9DSHaGe4yrG+oRRKhMZYpaJBQBJKMBEKQzhsrRBhr727208pU0fX9uX5Xa4ZDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"50530577b24a9bcc8aeef6ecefd29de7da31bb2191f911a0c0aa383a251eb8f7","last_reissued_at":"2026-07-05T02:30:59.322437Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:30:59.322437Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.10870","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:30:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vKm9uq1r48Nz/fM/gvD2m9ZeDK71ppl7dC8Sa91h124dZVKcKoZVfmTcP3IKzmiwevuV+NDsMY9c11oTjsFUAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T13:46:44.702179Z"},"content_sha256":"441d6f0b19d4c69d7b2605ed1e14042f8c3c4bbdfc5ed32f56cef1a288c66880","schema_version":"1.0","event_id":"sha256:441d6f0b19d4c69d7b2605ed1e14042f8c3c4bbdfc5ed32f56cef1a288c66880"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:KBJQK55SJKN4ZCXO63WO7UU547","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Arunselvan Ramaswamy, Eyke H\\\"ullermeier","submitted_at":"2020-08-25T07:59:20Z","abstract_excerpt":"Deep Q-Learning is an important reinforcement learning algorithm, which involves training a deep neural network, called Deep Q-Network (DQN), to approximate the well-known Q-function. Although wildly successful under laboratory conditions, serious gaps between theory and practice as well as a lack of formal guarantees prevent its use in the real world. Adopting a dynamical systems perspective, we provide a theoretical analysis of a popular version of Deep Q-Learning under realistic and verifiable assumptions. More specifically, we prove an important result on the convergence of the algorithm, "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.10870","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2008.10870/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:30:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HMwFwSrYnY1OBHZqWmwsdIdsMmCdsuqcqimZ3EqUVSm4NTGIrIXL8JpDBA4W+66Qavgx2SQ/SIj0FbFcWcssBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T13:46:44.702773Z"},"content_sha256":"2effd9b55890314f911ac09c37f029a5cb6e775169d5b6d3cebfd63a560f5d1d","schema_version":"1.0","event_id":"sha256:2effd9b55890314f911ac09c37f029a5cb6e775169d5b6d3cebfd63a560f5d1d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KBJQK55SJKN4ZCXO63WO7UU547/bundle.json","state_url":"https://pith.science/pith/KBJQK55SJKN4ZCXO63WO7UU547/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KBJQK55SJKN4ZCXO63WO7UU547/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-17T13:46:44Z","links":{"resolver":"https://pith.science/pith/KBJQK55SJKN4ZCXO63WO7UU547","bundle":"https://pith.science/pith/KBJQK55SJKN4ZCXO63WO7UU547/bundle.json","state":"https://pith.science/pith/KBJQK55SJKN4ZCXO63WO7UU547/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KBJQK55SJKN4ZCXO63WO7UU547/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:KBJQK55SJKN4ZCXO63WO7UU547","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":"ae4f5ba6600c233553d5ecf788cf50835e6f58f8517ea8b1528d461ce56672d5","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-25T07:59:20Z","title_canon_sha256":"db82fbf5469a91f12a3ab9fb870821c8907808389739d58a1adeef89039065dd"},"schema_version":"1.0","source":{"id":"2008.10870","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.10870","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"arxiv_version","alias_value":"2008.10870v2","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.10870","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"pith_short_12","alias_value":"KBJQK55SJKN4","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"pith_short_16","alias_value":"KBJQK55SJKN4ZCXO","created_at":"2026-07-05T02:30:59Z"},{"alias_kind":"pith_short_8","alias_value":"KBJQK55S","created_at":"2026-07-05T02:30:59Z"}],"graph_snapshots":[{"event_id":"sha256:2effd9b55890314f911ac09c37f029a5cb6e775169d5b6d3cebfd63a560f5d1d","target":"graph","created_at":"2026-07-05T02:30:59Z","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/2008.10870/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Q-Learning is an important reinforcement learning algorithm, which involves training a deep neural network, called Deep Q-Network (DQN), to approximate the well-known Q-function. Although wildly successful under laboratory conditions, serious gaps between theory and practice as well as a lack of formal guarantees prevent its use in the real world. Adopting a dynamical systems perspective, we provide a theoretical analysis of a popular version of Deep Q-Learning under realistic and verifiable assumptions. More specifically, we prove an important result on the convergence of the algorithm, ","authors_text":"Arunselvan Ramaswamy, Eyke H\\\"ullermeier","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-25T07:59:20Z","title":"Deep Q-Learning: Theoretical Insights from an Asymptotic Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.10870","kind":"arxiv","version":2},"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":"sha256:441d6f0b19d4c69d7b2605ed1e14042f8c3c4bbdfc5ed32f56cef1a288c66880","target":"record","created_at":"2026-07-05T02:30:59Z","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":"ae4f5ba6600c233553d5ecf788cf50835e6f58f8517ea8b1528d461ce56672d5","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-08-25T07:59:20Z","title_canon_sha256":"db82fbf5469a91f12a3ab9fb870821c8907808389739d58a1adeef89039065dd"},"schema_version":"1.0","source":{"id":"2008.10870","kind":"arxiv","version":2}},"canonical_sha256":"50530577b24a9bcc8aeef6ecefd29de7da31bb2191f911a0c0aa383a251eb8f7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"50530577b24a9bcc8aeef6ecefd29de7da31bb2191f911a0c0aa383a251eb8f7","first_computed_at":"2026-07-05T02:30:59.322437Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:30:59.322437Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"S2oCk5/zInQjqnBWG1P5fPzZ9DSHaGe4yrG+oRRKhMZYpaJBQBJKMBEKQzhsrRBhr727208pU0fX9uX5Xa4ZDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:30:59.322894Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.10870","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:441d6f0b19d4c69d7b2605ed1e14042f8c3c4bbdfc5ed32f56cef1a288c66880","sha256:2effd9b55890314f911ac09c37f029a5cb6e775169d5b6d3cebfd63a560f5d1d"],"state_sha256":"6dd111268d3cb42e67de9fbb3c7615c9abfb0ae9859b5136f17a3110b7a3ae67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9q9RmF+ZoKQz+lBIJ7crtPHD/BdGh/5yCZ+4Cwhyyx8YJqK3DrFJP9pNNDXTgfJ+d3NNMc19r3w1Y+KiCZNmCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T13:46:44.707173Z","bundle_sha256":"fd07b799809b61285747ff765077a00bb0afe37890979499cef51219001df7e6"}}