{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:A46CIMU4RVZQOJ3D5TJLCXLR5W","short_pith_number":"pith:A46CIMU4","canonical_record":{"source":{"id":"2307.03891","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-07-08T03:58:23Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"5692da306843b7c14807d27a9f6db00a8a79f3c8691f9f49b22f0e4d27df4300","abstract_canon_sha256":"859e7618e45df9e0614b652ce6fe4523f7702e260f7df71d4542b9a4955de117"},"schema_version":"1.0"},"canonical_sha256":"073c24329c8d73072763ecd2b15d71ed9cc11bc4909a5ddd530fd83b74567a03","source":{"kind":"arxiv","id":"2307.03891","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.03891","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"arxiv_version","alias_value":"2307.03891v4","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.03891","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"pith_short_12","alias_value":"A46CIMU4RVZQ","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"pith_short_16","alias_value":"A46CIMU4RVZQOJ3D","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"pith_short_8","alias_value":"A46CIMU4","created_at":"2026-07-05T07:03:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:A46CIMU4RVZQOJ3D5TJLCXLR5W","target":"record","payload":{"canonical_record":{"source":{"id":"2307.03891","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-07-08T03:58:23Z","cross_cats_sorted":["cs.MA"],"title_canon_sha256":"5692da306843b7c14807d27a9f6db00a8a79f3c8691f9f49b22f0e4d27df4300","abstract_canon_sha256":"859e7618e45df9e0614b652ce6fe4523f7702e260f7df71d4542b9a4955de117"},"schema_version":"1.0"},"canonical_sha256":"073c24329c8d73072763ecd2b15d71ed9cc11bc4909a5ddd530fd83b74567a03","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:03:28.892615Z","signature_b64":"qHkuMvpw77Mwa6ZSMPCN3h7r4GHqaEDNgRvL93dCkR5glyuop6RwRVTs3jzotPw7ykzulf2Ka6urwVozwQcwCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"073c24329c8d73072763ecd2b15d71ed9cc11bc4909a5ddd530fd83b74567a03","last_reissued_at":"2026-07-05T07:03:28.892077Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:03:28.892077Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2307.03891","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:03:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7X66HpBE8urM3qfQZyUOYoNxt8B3Y5IPoWxKK60S8teUX6liSUpUVWaEfusSMaWTZwK4vJkLjMovrwGCFt1zDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T06:45:11.854932Z"},"content_sha256":"7ac0d442ae9a45e4b74d73f9a5b71ff3e37fe38e8be5b14bec8ead4c411c27ba","schema_version":"1.0","event_id":"sha256:7ac0d442ae9a45e4b74d73f9a5b71ff3e37fe38e8be5b14bec8ead4c411c27ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:A46CIMU4RVZQOJ3D5TJLCXLR5W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithms","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.MA"],"primary_cat":"cs.RO","authors_text":"Harish Ravichandar, Meher Shashwat Nigam, Reza Torbati, Shivika Singh, Shubham Lohiya","submitted_at":"2023-07-08T03:58:23Z","abstract_excerpt":"Multi-Agent Reinforcement Learning (MARL) has enjoyed significant recent progress thanks, in part, to the integration of deep learning techniques for modeling interactions in complex environments. This is naturally starting to benefit multi-robot systems (MRS) in the form of multi-robot RL (MRRL). However, existing infrastructure to train and evaluate policies predominantly focus on the challenges of coordinating virtual agents, and ignore characteristics important to robotic systems. Few platforms support realistic robot dynamics, and fewer still can evaluate Sim2Real performance of learned b"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.03891","kind":"arxiv","version":4},"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/2307.03891/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":"2026-07-05T07:03:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BYx8wlkm5UC3pw7tycM/9u0X+zpbsw5yWXXj8gn0TYMF9q4BANPj5aXRuRnOiQDmuxE66b4KPcBGG7XwnNjpDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T06:45:11.855532Z"},"content_sha256":"dd9942884735c8daf177b03475371816bc303fc8229cc60f04becfad9ff5e94d","schema_version":"1.0","event_id":"sha256:dd9942884735c8daf177b03475371816bc303fc8229cc60f04becfad9ff5e94d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W/bundle.json","state_url":"https://pith.science/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W/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":"2026-08-23T06:45:11Z","links":{"resolver":"https://pith.science/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W","bundle":"https://pith.science/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W/bundle.json","state":"https://pith.science/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/A46CIMU4RVZQOJ3D5TJLCXLR5W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:A46CIMU4RVZQOJ3D5TJLCXLR5W","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":"859e7618e45df9e0614b652ce6fe4523f7702e260f7df71d4542b9a4955de117","cross_cats_sorted":["cs.MA"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-07-08T03:58:23Z","title_canon_sha256":"5692da306843b7c14807d27a9f6db00a8a79f3c8691f9f49b22f0e4d27df4300"},"schema_version":"1.0","source":{"id":"2307.03891","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2307.03891","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"arxiv_version","alias_value":"2307.03891v4","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.03891","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"pith_short_12","alias_value":"A46CIMU4RVZQ","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"pith_short_16","alias_value":"A46CIMU4RVZQOJ3D","created_at":"2026-07-05T07:03:28Z"},{"alias_kind":"pith_short_8","alias_value":"A46CIMU4","created_at":"2026-07-05T07:03:28Z"}],"graph_snapshots":[{"event_id":"sha256:dd9942884735c8daf177b03475371816bc303fc8229cc60f04becfad9ff5e94d","target":"graph","created_at":"2026-07-05T07:03:28Z","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/2307.03891/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-Agent Reinforcement Learning (MARL) has enjoyed significant recent progress thanks, in part, to the integration of deep learning techniques for modeling interactions in complex environments. This is naturally starting to benefit multi-robot systems (MRS) in the form of multi-robot RL (MRRL). However, existing infrastructure to train and evaluate policies predominantly focus on the challenges of coordinating virtual agents, and ignore characteristics important to robotic systems. Few platforms support realistic robot dynamics, and fewer still can evaluate Sim2Real performance of learned b","authors_text":"Harish Ravichandar, Meher Shashwat Nigam, Reza Torbati, Shivika Singh, Shubham Lohiya","cross_cats":["cs.MA"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-07-08T03:58:23Z","title":"MARBLER: An Open Platform for Standardized Evaluation of Multi-Robot Reinforcement Learning Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.03891","kind":"arxiv","version":4},"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":"sha256:7ac0d442ae9a45e4b74d73f9a5b71ff3e37fe38e8be5b14bec8ead4c411c27ba","target":"record","created_at":"2026-07-05T07:03:28Z","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":"859e7618e45df9e0614b652ce6fe4523f7702e260f7df71d4542b9a4955de117","cross_cats_sorted":["cs.MA"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2023-07-08T03:58:23Z","title_canon_sha256":"5692da306843b7c14807d27a9f6db00a8a79f3c8691f9f49b22f0e4d27df4300"},"schema_version":"1.0","source":{"id":"2307.03891","kind":"arxiv","version":4}},"canonical_sha256":"073c24329c8d73072763ecd2b15d71ed9cc11bc4909a5ddd530fd83b74567a03","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"073c24329c8d73072763ecd2b15d71ed9cc11bc4909a5ddd530fd83b74567a03","first_computed_at":"2026-07-05T07:03:28.892077Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:03:28.892077Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qHkuMvpw77Mwa6ZSMPCN3h7r4GHqaEDNgRvL93dCkR5glyuop6RwRVTs3jzotPw7ykzulf2Ka6urwVozwQcwCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:03:28.892615Z","signed_message":"canonical_sha256_bytes"},"source_id":"2307.03891","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7ac0d442ae9a45e4b74d73f9a5b71ff3e37fe38e8be5b14bec8ead4c411c27ba","sha256:dd9942884735c8daf177b03475371816bc303fc8229cc60f04becfad9ff5e94d"],"state_sha256":"13117847022d7ced9ad79ebb65f9e2a5a612a28a30670f2a559824612f83228f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N/S1+5QY7Syw6frNQ466cPTQ7OSlVcMRMn5s1PzwFf8rQy8/KvIrgCBpLjzhcb7O0gKMThNFyuajlOWBpZtoCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T06:45:11.860558Z","bundle_sha256":"530e53466d63b071b596e99c8650b851cb36095b4d79f47720836628d326f6e8"}}