{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GYSQ75E7OK2LY5VNWBPCUV5XXK","short_pith_number":"pith:GYSQ75E7","canonical_record":{"source":{"id":"2407.04889","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.GT","submitted_at":"2024-07-05T23:16:18Z","cross_cats_sorted":["cs.LG","cs.MA"],"title_canon_sha256":"0693591e8181a6faabf63661b272e814ea0ecab7c332029cadaf814ec3ab67a6","abstract_canon_sha256":"c9ca39a35eead1d1d0cf635b65ee02bc4cad6511ce7af134afb09c11fafcc080"},"schema_version":"1.0"},"canonical_sha256":"36250ff49f72b4bc76adb05e2a57b7ba8a27723c6f1ee2754f471c4dc8cf9bb0","source":{"kind":"arxiv","id":"2407.04889","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.04889","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"2407.04889v1","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.04889","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"GYSQ75E7OK2L","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"pith_short_16","alias_value":"GYSQ75E7OK2LY5VN","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"pith_short_8","alias_value":"GYSQ75E7","created_at":"2026-07-05T08:41:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GYSQ75E7OK2LY5VNWBPCUV5XXK","target":"record","payload":{"canonical_record":{"source":{"id":"2407.04889","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.GT","submitted_at":"2024-07-05T23:16:18Z","cross_cats_sorted":["cs.LG","cs.MA"],"title_canon_sha256":"0693591e8181a6faabf63661b272e814ea0ecab7c332029cadaf814ec3ab67a6","abstract_canon_sha256":"c9ca39a35eead1d1d0cf635b65ee02bc4cad6511ce7af134afb09c11fafcc080"},"schema_version":"1.0"},"canonical_sha256":"36250ff49f72b4bc76adb05e2a57b7ba8a27723c6f1ee2754f471c4dc8cf9bb0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:41:06.258654Z","signature_b64":"aZ3PSLoDXfkCWGJaql/XLuez8cs6EXX+Eb1nyDtEIgUC9mMb5+Ca0dac+buJXR+jsa2TOurS7w269xKODDu8Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36250ff49f72b4bc76adb05e2a57b7ba8a27723c6f1ee2754f471c4dc8cf9bb0","last_reissued_at":"2026-07-05T08:41:06.258163Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:41:06.258163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.04889","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p15IgVKcaS1w8U3EAnFJWQtBS0f2GinkjGFBrQE5+s1aGtBCpqpqdA/V/9vFsAriSNlU8YC5ebQfTaFwPYA0BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T09:59:13.431109Z"},"content_sha256":"c4d067cf9591ce25eef5436136de0c83fd3bf4da15255c37edbb698a9d1c2c61","schema_version":"1.0","event_id":"sha256:c4d067cf9591ce25eef5436136de0c83fd3bf4da15255c37edbb698a9d1c2c61"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GYSQ75E7OK2LY5VNWBPCUV5XXK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Maximizing utility in multi-agent environments by anticipating the behavior of other learners","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.LG","cs.MA"],"primary_cat":"cs.GT","authors_text":"Angelos Assos, Constantinos Daskalakis, Yuval Dagan","submitted_at":"2024-07-05T23:16:18Z","abstract_excerpt":"Learning algorithms are often used to make decisions in sequential decision-making environments. In multi-agent settings, the decisions of each agent can affect the utilities/losses of the other agents. Therefore, if an agent is good at anticipating the behavior of the other agents, in particular how they will make decisions in each round as a function of their experience that far, it could try to judiciously make its own decisions over the rounds of the interaction so as to influence the other agents to behave in a way that ultimately benefits its own utility. In this paper, we study repeated"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.04889","kind":"arxiv","version":1},"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/2407.04889/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":"2026-07-05T08:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L0wx4FUZeR4OrQLJVizsk9lETSWA7z38cBteMc08QqMQ55n+Gm+Z8hFFNeB12Ll2rKSIcqMfa7P10I1wygzUCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T09:59:13.431620Z"},"content_sha256":"88e65dee245f2bfcf3cc6702369c13dbd3b028479db49d43e4461a6b83e3f443","schema_version":"1.0","event_id":"sha256:88e65dee245f2bfcf3cc6702369c13dbd3b028479db49d43e4461a6b83e3f443"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK/bundle.json","state_url":"https://pith.science/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK/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":"2026-08-21T09:59:13Z","links":{"resolver":"https://pith.science/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK","bundle":"https://pith.science/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK/bundle.json","state":"https://pith.science/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GYSQ75E7OK2LY5VNWBPCUV5XXK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GYSQ75E7OK2LY5VNWBPCUV5XXK","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":"c9ca39a35eead1d1d0cf635b65ee02bc4cad6511ce7af134afb09c11fafcc080","cross_cats_sorted":["cs.LG","cs.MA"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.GT","submitted_at":"2024-07-05T23:16:18Z","title_canon_sha256":"0693591e8181a6faabf63661b272e814ea0ecab7c332029cadaf814ec3ab67a6"},"schema_version":"1.0","source":{"id":"2407.04889","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.04889","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"2407.04889v1","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.04889","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"GYSQ75E7OK2L","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"pith_short_16","alias_value":"GYSQ75E7OK2LY5VN","created_at":"2026-07-05T08:41:06Z"},{"alias_kind":"pith_short_8","alias_value":"GYSQ75E7","created_at":"2026-07-05T08:41:06Z"}],"graph_snapshots":[{"event_id":"sha256:88e65dee245f2bfcf3cc6702369c13dbd3b028479db49d43e4461a6b83e3f443","target":"graph","created_at":"2026-07-05T08:41:06Z","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/2407.04889/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Learning algorithms are often used to make decisions in sequential decision-making environments. In multi-agent settings, the decisions of each agent can affect the utilities/losses of the other agents. Therefore, if an agent is good at anticipating the behavior of the other agents, in particular how they will make decisions in each round as a function of their experience that far, it could try to judiciously make its own decisions over the rounds of the interaction so as to influence the other agents to behave in a way that ultimately benefits its own utility. In this paper, we study repeated","authors_text":"Angelos Assos, Constantinos Daskalakis, Yuval Dagan","cross_cats":["cs.LG","cs.MA"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.GT","submitted_at":"2024-07-05T23:16:18Z","title":"Maximizing utility in multi-agent environments by anticipating the behavior of other learners"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.04889","kind":"arxiv","version":1},"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:c4d067cf9591ce25eef5436136de0c83fd3bf4da15255c37edbb698a9d1c2c61","target":"record","created_at":"2026-07-05T08:41:06Z","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":"c9ca39a35eead1d1d0cf635b65ee02bc4cad6511ce7af134afb09c11fafcc080","cross_cats_sorted":["cs.LG","cs.MA"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.GT","submitted_at":"2024-07-05T23:16:18Z","title_canon_sha256":"0693591e8181a6faabf63661b272e814ea0ecab7c332029cadaf814ec3ab67a6"},"schema_version":"1.0","source":{"id":"2407.04889","kind":"arxiv","version":1}},"canonical_sha256":"36250ff49f72b4bc76adb05e2a57b7ba8a27723c6f1ee2754f471c4dc8cf9bb0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36250ff49f72b4bc76adb05e2a57b7ba8a27723c6f1ee2754f471c4dc8cf9bb0","first_computed_at":"2026-07-05T08:41:06.258163Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:41:06.258163Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aZ3PSLoDXfkCWGJaql/XLuez8cs6EXX+Eb1nyDtEIgUC9mMb5+Ca0dac+buJXR+jsa2TOurS7w269xKODDu8Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:41:06.258654Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.04889","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4d067cf9591ce25eef5436136de0c83fd3bf4da15255c37edbb698a9d1c2c61","sha256:88e65dee245f2bfcf3cc6702369c13dbd3b028479db49d43e4461a6b83e3f443"],"state_sha256":"c4a3957136206092dfe151094c08c7c0e88b7c8d800f20b5972d921849ea82bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/a7nwq2dHc6ZsWLAZoHYd4Miu5OYkImZabKZpYpk7dhuoIZRoxieF2NKj5KUJjCyUpaSWFJD3Sgk3UHqQAkXBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T09:59:13.436778Z","bundle_sha256":"69e8c444852345ba2cd18267008e68db69c9ceee523c66ff55e2e267d9bcd21a"}}