{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:RDL4RWQADWERMZXUSIQNOWNVYK","short_pith_number":"pith:RDL4RWQA","canonical_record":{"source":{"id":"2402.19420","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2024-02-29T18:16:13Z","cross_cats_sorted":["cs.AI","cs.MA"],"title_canon_sha256":"11c02724ea409686f36ca175a613e78a8cf60f6b732da3295d2bf9a0496acf32","abstract_canon_sha256":"1b35e6bea915d8eaa788918329c3afb8bc65962f3582f0f099ed32b6e57c733a"},"schema_version":"1.0"},"canonical_sha256":"88d7c8da001d891666f49220d759b5c2ad6116fb3da8d513450073670f9d9819","source":{"kind":"arxiv","id":"2402.19420","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.19420","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"arxiv_version","alias_value":"2402.19420v2","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.19420","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"pith_short_12","alias_value":"RDL4RWQADWER","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"pith_short_16","alias_value":"RDL4RWQADWERMZXU","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"pith_short_8","alias_value":"RDL4RWQA","created_at":"2026-07-05T08:47:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:RDL4RWQADWERMZXUSIQNOWNVYK","target":"record","payload":{"canonical_record":{"source":{"id":"2402.19420","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2024-02-29T18:16:13Z","cross_cats_sorted":["cs.AI","cs.MA"],"title_canon_sha256":"11c02724ea409686f36ca175a613e78a8cf60f6b732da3295d2bf9a0496acf32","abstract_canon_sha256":"1b35e6bea915d8eaa788918329c3afb8bc65962f3582f0f099ed32b6e57c733a"},"schema_version":"1.0"},"canonical_sha256":"88d7c8da001d891666f49220d759b5c2ad6116fb3da8d513450073670f9d9819","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:47:50.418208Z","signature_b64":"ssSxP/R/x4SMcZxjBwcxC/+WPOKPtpYMuHWAyMm1WCWeuy15Rn7S8f3CIIQiUm6MXka/793LdzynrCm4rxCcBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"88d7c8da001d891666f49220d759b5c2ad6116fb3da8d513450073670f9d9819","last_reissued_at":"2026-07-05T08:47:50.417789Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:47:50.417789Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.19420","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":"2026-07-05T08:47:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7ayYvkKpFRtL76btrdAgMLJHq55VlcQfGx7JkQohf8ucHWablFV1d6ebd4V0wVfAbmHp1Bz2u1h5PdrrqshNAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T07:13:28.271228Z"},"content_sha256":"7360025b7835b14f5e19167e1638f36e5974ea4186d3ea8769fab7ea4a42c4cc","schema_version":"1.0","event_id":"sha256:7360025b7835b14f5e19167e1638f36e5974ea4186d3ea8769fab7ea4a42c4cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:RDL4RWQADWERMZXUSIQNOWNVYK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding Iterative Combinatorial Auction Designs via Multi-Agent Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.MA"],"primary_cat":"cs.GT","authors_text":"Greg d'Eon, Kevin Leyton-Brown, Neil Newman","submitted_at":"2024-02-29T18:16:13Z","abstract_excerpt":"Iterative combinatorial auctions are widely used in high stakes settings such as spectrum auctions. Such auctions can be hard to analyze, making it difficult for bidders to determine how to behave and for designers to optimize auction rules to ensure desirable outcomes such as high revenue or welfare. In this paper, we investigate whether multi-agent reinforcement learning (MARL) algorithms can be used to understand iterative combinatorial auctions, given that these algorithms have recently shown empirical success in several other domains. We find that MARL can indeed benefit auction analysis,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.19420","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/2402.19420/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":"2026-07-05T08:47:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JkWK7/+yTkIAvixD77bas55doAjizx99pIQpgQp/8b/EDK3ZSUeSdlKHbkJUsF8MMdmnA3eTQbkIkCuoM8JwBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T07:13:28.271883Z"},"content_sha256":"4f2d425dee56bd5caf4719228119d71f12b85aacb6cbda0c4f74d9c06bb3a364","schema_version":"1.0","event_id":"sha256:4f2d425dee56bd5caf4719228119d71f12b85aacb6cbda0c4f74d9c06bb3a364"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RDL4RWQADWERMZXUSIQNOWNVYK/bundle.json","state_url":"https://pith.science/pith/RDL4RWQADWERMZXUSIQNOWNVYK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RDL4RWQADWERMZXUSIQNOWNVYK/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":"2026-07-09T07:13:28Z","links":{"resolver":"https://pith.science/pith/RDL4RWQADWERMZXUSIQNOWNVYK","bundle":"https://pith.science/pith/RDL4RWQADWERMZXUSIQNOWNVYK/bundle.json","state":"https://pith.science/pith/RDL4RWQADWERMZXUSIQNOWNVYK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RDL4RWQADWERMZXUSIQNOWNVYK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RDL4RWQADWERMZXUSIQNOWNVYK","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":"1b35e6bea915d8eaa788918329c3afb8bc65962f3582f0f099ed32b6e57c733a","cross_cats_sorted":["cs.AI","cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2024-02-29T18:16:13Z","title_canon_sha256":"11c02724ea409686f36ca175a613e78a8cf60f6b732da3295d2bf9a0496acf32"},"schema_version":"1.0","source":{"id":"2402.19420","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.19420","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"arxiv_version","alias_value":"2402.19420v2","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.19420","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"pith_short_12","alias_value":"RDL4RWQADWER","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"pith_short_16","alias_value":"RDL4RWQADWERMZXU","created_at":"2026-07-05T08:47:50Z"},{"alias_kind":"pith_short_8","alias_value":"RDL4RWQA","created_at":"2026-07-05T08:47:50Z"}],"graph_snapshots":[{"event_id":"sha256:4f2d425dee56bd5caf4719228119d71f12b85aacb6cbda0c4f74d9c06bb3a364","target":"graph","created_at":"2026-07-05T08:47:50Z","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/2402.19420/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Iterative combinatorial auctions are widely used in high stakes settings such as spectrum auctions. Such auctions can be hard to analyze, making it difficult for bidders to determine how to behave and for designers to optimize auction rules to ensure desirable outcomes such as high revenue or welfare. In this paper, we investigate whether multi-agent reinforcement learning (MARL) algorithms can be used to understand iterative combinatorial auctions, given that these algorithms have recently shown empirical success in several other domains. We find that MARL can indeed benefit auction analysis,","authors_text":"Greg d'Eon, Kevin Leyton-Brown, Neil Newman","cross_cats":["cs.AI","cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2024-02-29T18:16:13Z","title":"Understanding Iterative Combinatorial Auction Designs via Multi-Agent Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.19420","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":"sha256:7360025b7835b14f5e19167e1638f36e5974ea4186d3ea8769fab7ea4a42c4cc","target":"record","created_at":"2026-07-05T08:47:50Z","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":"1b35e6bea915d8eaa788918329c3afb8bc65962f3582f0f099ed32b6e57c733a","cross_cats_sorted":["cs.AI","cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.GT","submitted_at":"2024-02-29T18:16:13Z","title_canon_sha256":"11c02724ea409686f36ca175a613e78a8cf60f6b732da3295d2bf9a0496acf32"},"schema_version":"1.0","source":{"id":"2402.19420","kind":"arxiv","version":2}},"canonical_sha256":"88d7c8da001d891666f49220d759b5c2ad6116fb3da8d513450073670f9d9819","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"88d7c8da001d891666f49220d759b5c2ad6116fb3da8d513450073670f9d9819","first_computed_at":"2026-07-05T08:47:50.417789Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:47:50.417789Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ssSxP/R/x4SMcZxjBwcxC/+WPOKPtpYMuHWAyMm1WCWeuy15Rn7S8f3CIIQiUm6MXka/793LdzynrCm4rxCcBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:47:50.418208Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.19420","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7360025b7835b14f5e19167e1638f36e5974ea4186d3ea8769fab7ea4a42c4cc","sha256:4f2d425dee56bd5caf4719228119d71f12b85aacb6cbda0c4f74d9c06bb3a364"],"state_sha256":"bc800f0bd46ceb41ab9852af7ea7e8527611e01202c6a049325f475a1cf40630"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7UJZ5L1tV4fxnRa4kRHEH1pZYjQjMPOiOt0Ux4u4DK4qL4G4tX/nzEE2Phqh+VH/PE9wlSZhGuBlA1XwlUDKAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T07:13:28.277650Z","bundle_sha256":"ad3a437a4d24a03ddadfacbd1cf12eb9e3dc639fad5d4cf018982aa5f863eab3"}}