{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:RJKN7F42MLKK72GQ6GQ7DGZS6L","short_pith_number":"pith:RJKN7F42","canonical_record":{"source":{"id":"2010.02663","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2020-10-06T12:23:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c8451083ec9d9e5b1f116fcc271effefe51b5bc1bbb817a104e42b58a675086c","abstract_canon_sha256":"7ae6bfebf8491f6f9d83b4734ac6cf6894bea7a561aafc5d78e3a6a3684290a0"},"schema_version":"1.0"},"canonical_sha256":"8a54df979a62d4afe8d0f1a1f19b32f2e635ea9cc0f0a3254b2c1d9f2602758f","source":{"kind":"arxiv","id":"2010.02663","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.02663","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"arxiv_version","alias_value":"2010.02663v1","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.02663","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"pith_short_12","alias_value":"RJKN7F42MLKK","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"pith_short_16","alias_value":"RJKN7F42MLKK72GQ","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"pith_short_8","alias_value":"RJKN7F42","created_at":"2026-07-05T01:40:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:RJKN7F42MLKK72GQ6GQ7DGZS6L","target":"record","payload":{"canonical_record":{"source":{"id":"2010.02663","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2020-10-06T12:23:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c8451083ec9d9e5b1f116fcc271effefe51b5bc1bbb817a104e42b58a675086c","abstract_canon_sha256":"7ae6bfebf8491f6f9d83b4734ac6cf6894bea7a561aafc5d78e3a6a3684290a0"},"schema_version":"1.0"},"canonical_sha256":"8a54df979a62d4afe8d0f1a1f19b32f2e635ea9cc0f0a3254b2c1d9f2602758f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:40:52.545171Z","signature_b64":"Ez2onEa5u4K84n24vm4/ckjtGHV+kpUaW1joFzn+k7oWR7KMj3Pi0xhZVFKKFdxA1TjUuy4YPMl6ygj94TfBAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a54df979a62d4afe8d0f1a1f19b32f2e635ea9cc0f0a3254b2c1d9f2602758f","last_reissued_at":"2026-07-05T01:40:52.544838Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:40:52.544838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.02663","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":"2026-07-05T01:40:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Hcacv7ZjiAyScyiQyUMDfls8t+h4WAt4GyTRt/BtmSJNtfDnR+0seyUnNIxcLH42npjZHPQowQMY//MfaTGSAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T06:17:03.595551Z"},"content_sha256":"c2444c7bce61184033d3dd283004983edab76f478c55eec6dfbf88550e96958d","schema_version":"1.0","event_id":"sha256:c2444c7bce61184033d3dd283004983edab76f478c55eec6dfbf88550e96958d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:RJKN7F42MLKK72GQ6GQ7DGZS6L","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Heterogeneous Multi-Agent Reinforcement Learning for Unknown Environment Mapping","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.MA","authors_text":"Amanda Vu, Carrie Rebhuhn, Ceyer Wakilpoor, Patrick J. Martin","submitted_at":"2020-10-06T12:23:05Z","abstract_excerpt":"Reinforcement learning in heterogeneous multi-agent scenarios is important for real-world applications but presents challenges beyond those seen in homogeneous settings and simple benchmarks. In this work, we present an actor-critic algorithm that allows a team of heterogeneous agents to learn decentralized control policies for covering an unknown environment. This task is of interest to national security and emergency response organizations that would like to enhance situational awareness in hazardous areas by deploying teams of unmanned aerial vehicles. To solve this multi-agent coverage pat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.02663","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/2010.02663/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":"2026-07-05T01:40:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s+paTljzhG3annQlXjp7RGVreK5VRLIJx5wpnNoLDwxE0XHEu6pcFamRWpVNmvgWXE2/I/egqxhbKf+gP2C3Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T06:17:03.596777Z"},"content_sha256":"4d8bfb73a3fcbe6d18255871b7af717331c0444fae7a75b505561030f1fffd8d","schema_version":"1.0","event_id":"sha256:4d8bfb73a3fcbe6d18255871b7af717331c0444fae7a75b505561030f1fffd8d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L/bundle.json","state_url":"https://pith.science/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L/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":"2026-08-13T06:17:03Z","links":{"resolver":"https://pith.science/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L","bundle":"https://pith.science/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L/bundle.json","state":"https://pith.science/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RJKN7F42MLKK72GQ6GQ7DGZS6L/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:RJKN7F42MLKK72GQ6GQ7DGZS6L","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":"7ae6bfebf8491f6f9d83b4734ac6cf6894bea7a561aafc5d78e3a6a3684290a0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2020-10-06T12:23:05Z","title_canon_sha256":"c8451083ec9d9e5b1f116fcc271effefe51b5bc1bbb817a104e42b58a675086c"},"schema_version":"1.0","source":{"id":"2010.02663","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.02663","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"arxiv_version","alias_value":"2010.02663v1","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.02663","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"pith_short_12","alias_value":"RJKN7F42MLKK","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"pith_short_16","alias_value":"RJKN7F42MLKK72GQ","created_at":"2026-07-05T01:40:52Z"},{"alias_kind":"pith_short_8","alias_value":"RJKN7F42","created_at":"2026-07-05T01:40:52Z"}],"graph_snapshots":[{"event_id":"sha256:4d8bfb73a3fcbe6d18255871b7af717331c0444fae7a75b505561030f1fffd8d","target":"graph","created_at":"2026-07-05T01:40:52Z","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/2010.02663/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reinforcement learning in heterogeneous multi-agent scenarios is important for real-world applications but presents challenges beyond those seen in homogeneous settings and simple benchmarks. In this work, we present an actor-critic algorithm that allows a team of heterogeneous agents to learn decentralized control policies for covering an unknown environment. This task is of interest to national security and emergency response organizations that would like to enhance situational awareness in hazardous areas by deploying teams of unmanned aerial vehicles. To solve this multi-agent coverage pat","authors_text":"Amanda Vu, Carrie Rebhuhn, Ceyer Wakilpoor, Patrick J. Martin","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2020-10-06T12:23:05Z","title":"Heterogeneous Multi-Agent Reinforcement Learning for Unknown Environment Mapping"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.02663","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:c2444c7bce61184033d3dd283004983edab76f478c55eec6dfbf88550e96958d","target":"record","created_at":"2026-07-05T01:40:52Z","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":"7ae6bfebf8491f6f9d83b4734ac6cf6894bea7a561aafc5d78e3a6a3684290a0","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.MA","submitted_at":"2020-10-06T12:23:05Z","title_canon_sha256":"c8451083ec9d9e5b1f116fcc271effefe51b5bc1bbb817a104e42b58a675086c"},"schema_version":"1.0","source":{"id":"2010.02663","kind":"arxiv","version":1}},"canonical_sha256":"8a54df979a62d4afe8d0f1a1f19b32f2e635ea9cc0f0a3254b2c1d9f2602758f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a54df979a62d4afe8d0f1a1f19b32f2e635ea9cc0f0a3254b2c1d9f2602758f","first_computed_at":"2026-07-05T01:40:52.544838Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:40:52.544838Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ez2onEa5u4K84n24vm4/ckjtGHV+kpUaW1joFzn+k7oWR7KMj3Pi0xhZVFKKFdxA1TjUuy4YPMl6ygj94TfBAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:40:52.545171Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.02663","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c2444c7bce61184033d3dd283004983edab76f478c55eec6dfbf88550e96958d","sha256:4d8bfb73a3fcbe6d18255871b7af717331c0444fae7a75b505561030f1fffd8d"],"state_sha256":"df232c30ca50c69b828e1bbff5cdfeeb82e3af8ddc3b5e2c1592c51efdcf8805"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vN9dLCVX51mFyHjMXFnVamdNgjF1J8XjY23y04oW3NNsXcpLqcwkALlX0DDPlKWOhOxP9B0c5+fcGT4dMP4YBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T06:17:03.604866Z","bundle_sha256":"a592e306ff4ac0ae3879ba7a3d5e13d172e551b8bc6b619fbcdc7ca9247585b4"}}