{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:DT4POAQYH2KZEFAUAQJPHT2XXX","short_pith_number":"pith:DT4POAQY","canonical_record":{"source":{"id":"1906.00052","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-05-31T20:02:09Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"e3834b0d64f0feade9d12b075f56415c19467a87497d5c5ac4fe560918f7caf2","abstract_canon_sha256":"7c960ccca0abf885735056e0ca4e404dd717f53d64a0bfa6e0650fd7dc5268fe"},"schema_version":"1.0"},"canonical_sha256":"1cf8f702183e959214140412f3cf57bdc3dae73dfa098a58ff375719406a0a9c","source":{"kind":"arxiv","id":"1906.00052","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.00052","created_at":"2026-05-17T23:44:33Z"},{"alias_kind":"arxiv_version","alias_value":"1906.00052v1","created_at":"2026-05-17T23:44:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.00052","created_at":"2026-05-17T23:44:33Z"},{"alias_kind":"pith_short_12","alias_value":"DT4POAQYH2KZ","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"DT4POAQYH2KZEFAU","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"DT4POAQY","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:DT4POAQYH2KZEFAUAQJPHT2XXX","target":"record","payload":{"canonical_record":{"source":{"id":"1906.00052","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-05-31T20:02:09Z","cross_cats_sorted":["cs.LG","cs.RO"],"title_canon_sha256":"e3834b0d64f0feade9d12b075f56415c19467a87497d5c5ac4fe560918f7caf2","abstract_canon_sha256":"7c960ccca0abf885735056e0ca4e404dd717f53d64a0bfa6e0650fd7dc5268fe"},"schema_version":"1.0"},"canonical_sha256":"1cf8f702183e959214140412f3cf57bdc3dae73dfa098a58ff375719406a0a9c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:33.601390Z","signature_b64":"nG8nKhe22JtIN7+KO25+7Thz03PVWbv+3K8+LUz6baZpGhzqOMvTQ1YMDE3D0tsuPmsX3tmJ5vUgwzkI6w44Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1cf8f702183e959214140412f3cf57bdc3dae73dfa098a58ff375719406a0a9c","last_reissued_at":"2026-05-17T23:44:33.600740Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:33.600740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1906.00052","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":"2026-05-17T23:44:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WdAsAD8DKUm5opetPPwhZ1nwziCT1VCBwrrDbYLyGUaAFUXR+APlww1x/PIx6JjPx20N0d10wBiU2wnnqZFdBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T01:21:26.682514Z"},"content_sha256":"d4627c496bee1c1ae30d0442c9466bb289d6862bb167f17c7e9ad4925541ceec","schema_version":"1.0","event_id":"sha256:d4627c496bee1c1ae30d0442c9466bb289d6862bb167f17c7e9ad4925541ceec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:DT4POAQYH2KZEFAUAQJPHT2XXX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Training Detection-Range-Frugal Cooperative Collision Avoidance Models for Quadcopters via Neuroevolution","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.RO"],"primary_cat":"cs.NE","authors_text":"Amir Behjat, Krushang Gabani, Souma Chowdhury","submitted_at":"2019-05-31T20:02:09Z","abstract_excerpt":"Cooperative autonomous approaches to avoiding collisions among small Unmanned Aerial Vehicles (UAVs) is central to safe integration of UAVs within the civilian airspace. One potential online cooperative approach is the concept of reciprocal actions, where both UAVs take pre-trained mutually coherent actions that do not require active online coordination (thereby avoiding the computational burden and risk associated with it). This paper presents a learning based approach to train such reciprocal maneuvers. Neuroevolution, which uses evolutionary algorithms to simultaneously optimize the topolog"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.00052","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":""},"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":"2026-05-17T23:44:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DSvymSkjLQDbkpPDp72VaGpMYn2J0gWZSAbjJc76ogP6f2yZ210Jwmt1XjHrPUvZGm8jf5YnGoseELxE+C4JBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T01:21:26.682862Z"},"content_sha256":"e19e9298aef9d998e34e8071aca16e4f124bc8c3a2e74726f35a0547a07d69a6","schema_version":"1.0","event_id":"sha256:e19e9298aef9d998e34e8071aca16e4f124bc8c3a2e74726f35a0547a07d69a6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DT4POAQYH2KZEFAUAQJPHT2XXX/bundle.json","state_url":"https://pith.science/pith/DT4POAQYH2KZEFAUAQJPHT2XXX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DT4POAQYH2KZEFAUAQJPHT2XXX/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":"2026-06-26T01:21:26Z","links":{"resolver":"https://pith.science/pith/DT4POAQYH2KZEFAUAQJPHT2XXX","bundle":"https://pith.science/pith/DT4POAQYH2KZEFAUAQJPHT2XXX/bundle.json","state":"https://pith.science/pith/DT4POAQYH2KZEFAUAQJPHT2XXX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DT4POAQYH2KZEFAUAQJPHT2XXX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:DT4POAQYH2KZEFAUAQJPHT2XXX","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":"7c960ccca0abf885735056e0ca4e404dd717f53d64a0bfa6e0650fd7dc5268fe","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-05-31T20:02:09Z","title_canon_sha256":"e3834b0d64f0feade9d12b075f56415c19467a87497d5c5ac4fe560918f7caf2"},"schema_version":"1.0","source":{"id":"1906.00052","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1906.00052","created_at":"2026-05-17T23:44:33Z"},{"alias_kind":"arxiv_version","alias_value":"1906.00052v1","created_at":"2026-05-17T23:44:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.00052","created_at":"2026-05-17T23:44:33Z"},{"alias_kind":"pith_short_12","alias_value":"DT4POAQYH2KZ","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"DT4POAQYH2KZEFAU","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"DT4POAQY","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:e19e9298aef9d998e34e8071aca16e4f124bc8c3a2e74726f35a0547a07d69a6","target":"graph","created_at":"2026-05-17T23:44:33Z","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"},"paper":{"abstract_excerpt":"Cooperative autonomous approaches to avoiding collisions among small Unmanned Aerial Vehicles (UAVs) is central to safe integration of UAVs within the civilian airspace. One potential online cooperative approach is the concept of reciprocal actions, where both UAVs take pre-trained mutually coherent actions that do not require active online coordination (thereby avoiding the computational burden and risk associated with it). This paper presents a learning based approach to train such reciprocal maneuvers. Neuroevolution, which uses evolutionary algorithms to simultaneously optimize the topolog","authors_text":"Amir Behjat, Krushang Gabani, Souma Chowdhury","cross_cats":["cs.LG","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-05-31T20:02:09Z","title":"Training Detection-Range-Frugal Cooperative Collision Avoidance Models for Quadcopters via Neuroevolution"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.00052","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:d4627c496bee1c1ae30d0442c9466bb289d6862bb167f17c7e9ad4925541ceec","target":"record","created_at":"2026-05-17T23:44:33Z","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":"7c960ccca0abf885735056e0ca4e404dd717f53d64a0bfa6e0650fd7dc5268fe","cross_cats_sorted":["cs.LG","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2019-05-31T20:02:09Z","title_canon_sha256":"e3834b0d64f0feade9d12b075f56415c19467a87497d5c5ac4fe560918f7caf2"},"schema_version":"1.0","source":{"id":"1906.00052","kind":"arxiv","version":1}},"canonical_sha256":"1cf8f702183e959214140412f3cf57bdc3dae73dfa098a58ff375719406a0a9c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1cf8f702183e959214140412f3cf57bdc3dae73dfa098a58ff375719406a0a9c","first_computed_at":"2026-05-17T23:44:33.600740Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:44:33.600740Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nG8nKhe22JtIN7+KO25+7Thz03PVWbv+3K8+LUz6baZpGhzqOMvTQ1YMDE3D0tsuPmsX3tmJ5vUgwzkI6w44Dg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:44:33.601390Z","signed_message":"canonical_sha256_bytes"},"source_id":"1906.00052","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4627c496bee1c1ae30d0442c9466bb289d6862bb167f17c7e9ad4925541ceec","sha256:e19e9298aef9d998e34e8071aca16e4f124bc8c3a2e74726f35a0547a07d69a6"],"state_sha256":"706e670037755317b7230c0e3c712680a884ccfe9569dc214330c05e40de0de5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sGEGhay4TSaqYj7x8UgCJR6l3Ign/XyTiqiwLt9VR774b39fTgngrRyMqKW/XtrbIzM25eaxYVqd3qVcu3cwAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T01:21:26.684801Z","bundle_sha256":"e53dfa135f0520a40bc08fe04ad438e72fb59d13b2ce5f64077e8b1db6f670ec"}}