{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:X46Y6ZSCF4HHQEOACYZPMREEYB","short_pith_number":"pith:X46Y6ZSC","canonical_record":{"source":{"id":"2306.11846","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-06-20T18:56:25Z","cross_cats_sorted":["cs.LG","cs.MA","stat.ME"],"title_canon_sha256":"a496222811c400d35234ead2cd4fcabc3693f7b50f9f7822cebb21f1a26de0eb","abstract_canon_sha256":"7eb916a5340f8e4f50c43127ce26da20d0dd61b9367e4b3c616c22314787d819"},"schema_version":"1.0"},"canonical_sha256":"bf3d8f66422f0e7811c01632f64484c047063cc5d469af8dd4e9c97d35e7edf9","source":{"kind":"arxiv","id":"2306.11846","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.11846","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"arxiv_version","alias_value":"2306.11846v1","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.11846","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"pith_short_12","alias_value":"X46Y6ZSCF4HH","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"pith_short_16","alias_value":"X46Y6ZSCF4HHQEOA","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"pith_short_8","alias_value":"X46Y6ZSC","created_at":"2026-07-05T06:23:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:X46Y6ZSCF4HHQEOACYZPMREEYB","target":"record","payload":{"canonical_record":{"source":{"id":"2306.11846","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-06-20T18:56:25Z","cross_cats_sorted":["cs.LG","cs.MA","stat.ME"],"title_canon_sha256":"a496222811c400d35234ead2cd4fcabc3693f7b50f9f7822cebb21f1a26de0eb","abstract_canon_sha256":"7eb916a5340f8e4f50c43127ce26da20d0dd61b9367e4b3c616c22314787d819"},"schema_version":"1.0"},"canonical_sha256":"bf3d8f66422f0e7811c01632f64484c047063cc5d469af8dd4e9c97d35e7edf9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:23:07.505271Z","signature_b64":"5P3J/V5UOk2UnbKgRBLKafJI4y1VuHWcrfUDNMU7DEvYN5pt/sZ1cPBKphW6uS52jL76Dl5m7k71DNKCqCYFAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf3d8f66422f0e7811c01632f64484c047063cc5d469af8dd4e9c97d35e7edf9","last_reissued_at":"2026-07-05T06:23:07.504930Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:23:07.504930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.11846","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":"2026-07-05T06:23:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XMtu1EH1jiEvubyhEzeModkTFa8uTT8z96yA6SdX2FH9pJfxWXXcbH5oZBsnmz+C4FOXJNRuw4dWmKxMZYsxAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:29:51.696894Z"},"content_sha256":"52f677cdc20924b84921395de632cb42eda3077a6d52d13c06fbdd0370605c79","schema_version":"1.0","event_id":"sha256:52f677cdc20924b84921395de632cb42eda3077a6d52d13c06fbdd0370605c79"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:X46Y6ZSCF4HHQEOACYZPMREEYB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Discovering Causality for Efficient Cooperation in Multi-Agent Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.MA","stat.ME"],"primary_cat":"cs.AI","authors_text":"Corentin Artaud, Rafael Pina, Varuna De Silva","submitted_at":"2023-06-20T18:56:25Z","abstract_excerpt":"In cooperative Multi-Agent Reinforcement Learning (MARL) agents are required to learn behaviours as a team to achieve a common goal. However, while learning a task, some agents may end up learning sub-optimal policies, not contributing to the objective of the team. Such agents are called lazy agents due to their non-cooperative behaviours that may arise from failing to understand whether they caused the rewards. As a consequence, we observe that the emergence of cooperative behaviours is not necessarily a byproduct of being able to solve a task as a team. In this paper, we investigate the appl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.11846","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/2306.11846/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":"2026-07-05T06:23:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RudnBVR57WPc5WQexZxaXWnN5H3DNghuDDAZFqeMEgNWfXqjPklEJq0UwJnH+pjHjUMCloaRZXNcWI8wyLHVBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:29:51.697896Z"},"content_sha256":"2765d4fc8025063b2acf2fced7dc7930ee863477298c4b713e1a8c9bac70f335","schema_version":"1.0","event_id":"sha256:2765d4fc8025063b2acf2fced7dc7930ee863477298c4b713e1a8c9bac70f335"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X46Y6ZSCF4HHQEOACYZPMREEYB/bundle.json","state_url":"https://pith.science/pith/X46Y6ZSCF4HHQEOACYZPMREEYB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X46Y6ZSCF4HHQEOACYZPMREEYB/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":"2026-08-09T19:29:51Z","links":{"resolver":"https://pith.science/pith/X46Y6ZSCF4HHQEOACYZPMREEYB","bundle":"https://pith.science/pith/X46Y6ZSCF4HHQEOACYZPMREEYB/bundle.json","state":"https://pith.science/pith/X46Y6ZSCF4HHQEOACYZPMREEYB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X46Y6ZSCF4HHQEOACYZPMREEYB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:X46Y6ZSCF4HHQEOACYZPMREEYB","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":"7eb916a5340f8e4f50c43127ce26da20d0dd61b9367e4b3c616c22314787d819","cross_cats_sorted":["cs.LG","cs.MA","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-06-20T18:56:25Z","title_canon_sha256":"a496222811c400d35234ead2cd4fcabc3693f7b50f9f7822cebb21f1a26de0eb"},"schema_version":"1.0","source":{"id":"2306.11846","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.11846","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"arxiv_version","alias_value":"2306.11846v1","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.11846","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"pith_short_12","alias_value":"X46Y6ZSCF4HH","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"pith_short_16","alias_value":"X46Y6ZSCF4HHQEOA","created_at":"2026-07-05T06:23:07Z"},{"alias_kind":"pith_short_8","alias_value":"X46Y6ZSC","created_at":"2026-07-05T06:23:07Z"}],"graph_snapshots":[{"event_id":"sha256:2765d4fc8025063b2acf2fced7dc7930ee863477298c4b713e1a8c9bac70f335","target":"graph","created_at":"2026-07-05T06:23:07Z","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/2306.11846/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In cooperative Multi-Agent Reinforcement Learning (MARL) agents are required to learn behaviours as a team to achieve a common goal. However, while learning a task, some agents may end up learning sub-optimal policies, not contributing to the objective of the team. Such agents are called lazy agents due to their non-cooperative behaviours that may arise from failing to understand whether they caused the rewards. As a consequence, we observe that the emergence of cooperative behaviours is not necessarily a byproduct of being able to solve a task as a team. In this paper, we investigate the appl","authors_text":"Corentin Artaud, Rafael Pina, Varuna De Silva","cross_cats":["cs.LG","cs.MA","stat.ME"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-06-20T18:56:25Z","title":"Discovering Causality for Efficient Cooperation in Multi-Agent Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.11846","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":"sha256:52f677cdc20924b84921395de632cb42eda3077a6d52d13c06fbdd0370605c79","target":"record","created_at":"2026-07-05T06:23:07Z","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":"7eb916a5340f8e4f50c43127ce26da20d0dd61b9367e4b3c616c22314787d819","cross_cats_sorted":["cs.LG","cs.MA","stat.ME"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2023-06-20T18:56:25Z","title_canon_sha256":"a496222811c400d35234ead2cd4fcabc3693f7b50f9f7822cebb21f1a26de0eb"},"schema_version":"1.0","source":{"id":"2306.11846","kind":"arxiv","version":1}},"canonical_sha256":"bf3d8f66422f0e7811c01632f64484c047063cc5d469af8dd4e9c97d35e7edf9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf3d8f66422f0e7811c01632f64484c047063cc5d469af8dd4e9c97d35e7edf9","first_computed_at":"2026-07-05T06:23:07.504930Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:23:07.504930Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5P3J/V5UOk2UnbKgRBLKafJI4y1VuHWcrfUDNMU7DEvYN5pt/sZ1cPBKphW6uS52jL76Dl5m7k71DNKCqCYFAA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:23:07.505271Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.11846","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:52f677cdc20924b84921395de632cb42eda3077a6d52d13c06fbdd0370605c79","sha256:2765d4fc8025063b2acf2fced7dc7930ee863477298c4b713e1a8c9bac70f335"],"state_sha256":"1da7d78f6e6c85c5e1367f8f9ed4a22805b51001aa71efc709e1815415c24e1a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sB/rmFrhMEWHlb6z6vEHJ2d1mzCJueayH0HmkSBH8XupPvHGZjXO/W2aqRildFaslk18psc5DlDw37H5eeoSBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T19:29:51.704406Z","bundle_sha256":"6caed1ac6a92d39e1316631f7f6ba0ffec42499a3ed721683a7b726440dad5f5"}}