{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UWIKKTY67QGWWWI6YNYN6LZS6U","short_pith_number":"pith:UWIKKTY6","canonical_record":{"source":{"id":"2403.15341","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-22T16:50:56Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"3bdd8c36d5f6edad90c48605b7c75f8fcc5422751bb9ecf58f003995a8d18881","abstract_canon_sha256":"3ea4ebe4c7f990ad571c90569fadc96d1fbda6fc81ccf1e9d1b7b975ff34f5b4"},"schema_version":"1.0"},"canonical_sha256":"a590a54f1efc0d6b591ec370df2f32f509218a6cdf68a4473c10a7add7ec81f9","source":{"kind":"arxiv","id":"2403.15341","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.15341","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"arxiv_version","alias_value":"2403.15341v1","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.15341","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"pith_short_12","alias_value":"UWIKKTY67QGW","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"pith_short_16","alias_value":"UWIKKTY67QGWWWI6","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"pith_short_8","alias_value":"UWIKKTY6","created_at":"2026-07-05T07:59:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UWIKKTY67QGWWWI6YNYN6LZS6U","target":"record","payload":{"canonical_record":{"source":{"id":"2403.15341","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-22T16:50:56Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"3bdd8c36d5f6edad90c48605b7c75f8fcc5422751bb9ecf58f003995a8d18881","abstract_canon_sha256":"3ea4ebe4c7f990ad571c90569fadc96d1fbda6fc81ccf1e9d1b7b975ff34f5b4"},"schema_version":"1.0"},"canonical_sha256":"a590a54f1efc0d6b591ec370df2f32f509218a6cdf68a4473c10a7add7ec81f9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:33.287490Z","signature_b64":"IKefgfOH0wbOa606ATb6bGVmgura5pSIvNU0KgA/Bm9oHnEg8b5pUi0pjhkThx5WQTqjjJoqkOXKXsWPOFv1AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a590a54f1efc0d6b591ec370df2f32f509218a6cdf68a4473c10a7add7ec81f9","last_reissued_at":"2026-07-05T07:59:33.287077Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:33.287077Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.15341","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":"2026-07-05T07:59:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qfmOxxizyHiPNEFgMU/n3Pbhlh4pNzjor8wfofS9sfzBESzqcCJd/tSBhzCnc42PDTh0c9UpYIorS7iCz8APAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T14:20:40.937569Z"},"content_sha256":"ff91dbc735ae030bfa0791645cbc4d85fef7483b519f9862ad30d2947c8b190f","schema_version":"1.0","event_id":"sha256:ff91dbc735ae030bfa0791645cbc4d85fef7483b519f9862ad30d2947c8b190f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UWIKKTY67QGWWWI6YNYN6LZS6U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Collaborative AI Teaming in Unknown Environments via Active Goal Deduction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.AI","authors_text":"Hanhan Zhou, Mahdi Imani, Taeyoung Lee, Tian Lan, Zuyuan Zhang","submitted_at":"2024-03-22T16:50:56Z","abstract_excerpt":"With the advancements of artificial intelligence (AI), we're seeing more scenarios that require AI to work closely with other agents, whose goals and strategies might not be known beforehand. However, existing approaches for training collaborative agents often require defined and known reward signals and cannot address the problem of teaming with unknown agents that often have latent objectives/rewards. In response to this challenge, we propose teaming with unknown agents framework, which leverages kernel density Bayesian inverse learning method for active goal deduction and utilizes pre-train"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.15341","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/2403.15341/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":"2026-07-05T07:59:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gW+ASOPPLPbAqezs4z57U5f9XqUa2+Fub9JhQ56xDvWjSM2FgPF2wLz7Y8sPdnFl1OCWki1fK5j8m5hYKeziBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T14:20:40.938117Z"},"content_sha256":"fba1792e499d6cdc7bdca533cdf746da7d6c36492a3f99ec41c07164f7b37207","schema_version":"1.0","event_id":"sha256:fba1792e499d6cdc7bdca533cdf746da7d6c36492a3f99ec41c07164f7b37207"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UWIKKTY67QGWWWI6YNYN6LZS6U/bundle.json","state_url":"https://pith.science/pith/UWIKKTY67QGWWWI6YNYN6LZS6U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UWIKKTY67QGWWWI6YNYN6LZS6U/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":"2026-08-10T14:20:40Z","links":{"resolver":"https://pith.science/pith/UWIKKTY67QGWWWI6YNYN6LZS6U","bundle":"https://pith.science/pith/UWIKKTY67QGWWWI6YNYN6LZS6U/bundle.json","state":"https://pith.science/pith/UWIKKTY67QGWWWI6YNYN6LZS6U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UWIKKTY67QGWWWI6YNYN6LZS6U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UWIKKTY67QGWWWI6YNYN6LZS6U","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":"3ea4ebe4c7f990ad571c90569fadc96d1fbda6fc81ccf1e9d1b7b975ff34f5b4","cross_cats_sorted":["cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-22T16:50:56Z","title_canon_sha256":"3bdd8c36d5f6edad90c48605b7c75f8fcc5422751bb9ecf58f003995a8d18881"},"schema_version":"1.0","source":{"id":"2403.15341","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.15341","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"arxiv_version","alias_value":"2403.15341v1","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.15341","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"pith_short_12","alias_value":"UWIKKTY67QGW","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"pith_short_16","alias_value":"UWIKKTY67QGWWWI6","created_at":"2026-07-05T07:59:33Z"},{"alias_kind":"pith_short_8","alias_value":"UWIKKTY6","created_at":"2026-07-05T07:59:33Z"}],"graph_snapshots":[{"event_id":"sha256:fba1792e499d6cdc7bdca533cdf746da7d6c36492a3f99ec41c07164f7b37207","target":"graph","created_at":"2026-07-05T07:59:33Z","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/2403.15341/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the advancements of artificial intelligence (AI), we're seeing more scenarios that require AI to work closely with other agents, whose goals and strategies might not be known beforehand. However, existing approaches for training collaborative agents often require defined and known reward signals and cannot address the problem of teaming with unknown agents that often have latent objectives/rewards. In response to this challenge, we propose teaming with unknown agents framework, which leverages kernel density Bayesian inverse learning method for active goal deduction and utilizes pre-train","authors_text":"Hanhan Zhou, Mahdi Imani, Taeyoung Lee, Tian Lan, Zuyuan Zhang","cross_cats":["cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-22T16:50:56Z","title":"Collaborative AI Teaming in Unknown Environments via Active Goal Deduction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.15341","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:ff91dbc735ae030bfa0791645cbc4d85fef7483b519f9862ad30d2947c8b190f","target":"record","created_at":"2026-07-05T07:59:33Z","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":"3ea4ebe4c7f990ad571c90569fadc96d1fbda6fc81ccf1e9d1b7b975ff34f5b4","cross_cats_sorted":["cs.MA"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-03-22T16:50:56Z","title_canon_sha256":"3bdd8c36d5f6edad90c48605b7c75f8fcc5422751bb9ecf58f003995a8d18881"},"schema_version":"1.0","source":{"id":"2403.15341","kind":"arxiv","version":1}},"canonical_sha256":"a590a54f1efc0d6b591ec370df2f32f509218a6cdf68a4473c10a7add7ec81f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a590a54f1efc0d6b591ec370df2f32f509218a6cdf68a4473c10a7add7ec81f9","first_computed_at":"2026-07-05T07:59:33.287077Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:59:33.287077Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IKefgfOH0wbOa606ATb6bGVmgura5pSIvNU0KgA/Bm9oHnEg8b5pUi0pjhkThx5WQTqjjJoqkOXKXsWPOFv1AA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:59:33.287490Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.15341","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ff91dbc735ae030bfa0791645cbc4d85fef7483b519f9862ad30d2947c8b190f","sha256:fba1792e499d6cdc7bdca533cdf746da7d6c36492a3f99ec41c07164f7b37207"],"state_sha256":"dba6309b7e7c4d6c8c1e3a603a558e33f5fac224987af27903e37a54ea52b67c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Skk03RINf4xZUy4rN4f1nnDIteF58WKWedHel1SSplPaDdj4r9Qmf8q5uQKsG2QORy0P8GkqfyQFG9vLPPaBCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T14:20:40.943143Z","bundle_sha256":"4bf571811e031b05eaa43acf12982a06481518beab715429087fc6b7b9129851"}}