{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:T33JJKFPEDLNORPZQG5KZ5VF6S","short_pith_number":"pith:T33JJKFP","canonical_record":{"source":{"id":"2403.14028","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-20T22:56:11Z","cross_cats_sorted":["cs.SY","math.CO","math.OC"],"title_canon_sha256":"dc65446f4b7c73c8f6fa42897381253441fa8c136325a616526e194cdcb1e482","abstract_canon_sha256":"6eb2b725bb52469230cc2949d270910337f141ac73f60684a6cc4794b87458c0"},"schema_version":"1.0"},"canonical_sha256":"9ef694a8af20d6d745f981baacf6a5f49b1f15ae54481f7f3e4e69d859270e3a","source":{"kind":"arxiv","id":"2403.14028","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.14028","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"arxiv_version","alias_value":"2403.14028v2","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14028","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"pith_short_12","alias_value":"T33JJKFPEDLN","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"pith_short_16","alias_value":"T33JJKFPEDLNORPZ","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"pith_short_8","alias_value":"T33JJKFP","created_at":"2026-07-05T07:59:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:T33JJKFPEDLNORPZQG5KZ5VF6S","target":"record","payload":{"canonical_record":{"source":{"id":"2403.14028","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-20T22:56:11Z","cross_cats_sorted":["cs.SY","math.CO","math.OC"],"title_canon_sha256":"dc65446f4b7c73c8f6fa42897381253441fa8c136325a616526e194cdcb1e482","abstract_canon_sha256":"6eb2b725bb52469230cc2949d270910337f141ac73f60684a6cc4794b87458c0"},"schema_version":"1.0"},"canonical_sha256":"9ef694a8af20d6d745f981baacf6a5f49b1f15ae54481f7f3e4e69d859270e3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:59:36.408774Z","signature_b64":"auhUHDQa4pH0dD6r/Fr0ICyyZ6YC4muSVr9RIj7Xn0e5DTry7TfxlHlpEKBep2D9Z/TxEDrh9Oli9449RVTHAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ef694a8af20d6d745f981baacf6a5f49b1f15ae54481f7f3e4e69d859270e3a","last_reissued_at":"2026-07-05T07:59:36.408285Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:59:36.408285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.14028","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:59:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aF40Xh8womL6LNzL23bl+5EYxQiVYVvf01FrPvDqvPpquhYtC8RBIInL6VFwIwn8XhOOZoJg7AGphl2QIu7RCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T20:56:26.738383Z"},"content_sha256":"3d49df4bb7123d40aa6ea55e8f268b891dcb5505f7c7092a7944b0740553411a","schema_version":"1.0","event_id":"sha256:3d49df4bb7123d40aa6ea55e8f268b891dcb5505f7c7092a7944b0740553411a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:T33JJKFPEDLNORPZQG5KZ5VF6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Performance-Guaranteed Solutions for Multi-Agent Optimal Coverage Problems using Submodularity, Curvature, and Greedy Algorithms","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY","math.CO","math.OC"],"primary_cat":"eess.SY","authors_text":"Christos G. Cassandras, Shirantha Welikala","submitted_at":"2024-03-20T22:56:11Z","abstract_excerpt":"We consider a class of multi-agent optimal coverage problems in which the goal is to determine the optimal placement of a group of agents in a given mission space so that they maximize a coverage objective that represents a blend of individual and collaborative event detection capabilities. This class of problems is extremely challenging due to the non-convex nature of the mission space and of the coverage objective. With this motivation, greedy algorithms are often used as means of getting feasible coverage solutions efficiently. Even though such greedy solutions are suboptimal, the submodula"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14028","kind":"arxiv","version":2},"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/2403.14028/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":"2026-07-05T07:59:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e6Yk1iX2Ie13xavKPX7Ou5r7R7SILk0xD6v1CM5lttLWl1ZWle2lKYRCUsxX5fJ6PMyzX+03ZJAxXJxegSr8BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T20:56:26.738778Z"},"content_sha256":"be18b7f727ec69b9478cdccacb3f2061512d78fa5d85832d83782bee49c0c1bc","schema_version":"1.0","event_id":"sha256:be18b7f727ec69b9478cdccacb3f2061512d78fa5d85832d83782bee49c0c1bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T33JJKFPEDLNORPZQG5KZ5VF6S/bundle.json","state_url":"https://pith.science/pith/T33JJKFPEDLNORPZQG5KZ5VF6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T33JJKFPEDLNORPZQG5KZ5VF6S/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":"2026-07-28T20:56:26Z","links":{"resolver":"https://pith.science/pith/T33JJKFPEDLNORPZQG5KZ5VF6S","bundle":"https://pith.science/pith/T33JJKFPEDLNORPZQG5KZ5VF6S/bundle.json","state":"https://pith.science/pith/T33JJKFPEDLNORPZQG5KZ5VF6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T33JJKFPEDLNORPZQG5KZ5VF6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:T33JJKFPEDLNORPZQG5KZ5VF6S","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":"6eb2b725bb52469230cc2949d270910337f141ac73f60684a6cc4794b87458c0","cross_cats_sorted":["cs.SY","math.CO","math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-20T22:56:11Z","title_canon_sha256":"dc65446f4b7c73c8f6fa42897381253441fa8c136325a616526e194cdcb1e482"},"schema_version":"1.0","source":{"id":"2403.14028","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.14028","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"arxiv_version","alias_value":"2403.14028v2","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.14028","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"pith_short_12","alias_value":"T33JJKFPEDLN","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"pith_short_16","alias_value":"T33JJKFPEDLNORPZ","created_at":"2026-07-05T07:59:36Z"},{"alias_kind":"pith_short_8","alias_value":"T33JJKFP","created_at":"2026-07-05T07:59:36Z"}],"graph_snapshots":[{"event_id":"sha256:be18b7f727ec69b9478cdccacb3f2061512d78fa5d85832d83782bee49c0c1bc","target":"graph","created_at":"2026-07-05T07:59:36Z","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/2403.14028/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We consider a class of multi-agent optimal coverage problems in which the goal is to determine the optimal placement of a group of agents in a given mission space so that they maximize a coverage objective that represents a blend of individual and collaborative event detection capabilities. This class of problems is extremely challenging due to the non-convex nature of the mission space and of the coverage objective. With this motivation, greedy algorithms are often used as means of getting feasible coverage solutions efficiently. Even though such greedy solutions are suboptimal, the submodula","authors_text":"Christos G. Cassandras, Shirantha Welikala","cross_cats":["cs.SY","math.CO","math.OC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-20T22:56:11Z","title":"Performance-Guaranteed Solutions for Multi-Agent Optimal Coverage Problems using Submodularity, Curvature, and Greedy Algorithms"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.14028","kind":"arxiv","version":2},"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":"sha256:3d49df4bb7123d40aa6ea55e8f268b891dcb5505f7c7092a7944b0740553411a","target":"record","created_at":"2026-07-05T07:59:36Z","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":"6eb2b725bb52469230cc2949d270910337f141ac73f60684a6cc4794b87458c0","cross_cats_sorted":["cs.SY","math.CO","math.OC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2024-03-20T22:56:11Z","title_canon_sha256":"dc65446f4b7c73c8f6fa42897381253441fa8c136325a616526e194cdcb1e482"},"schema_version":"1.0","source":{"id":"2403.14028","kind":"arxiv","version":2}},"canonical_sha256":"9ef694a8af20d6d745f981baacf6a5f49b1f15ae54481f7f3e4e69d859270e3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ef694a8af20d6d745f981baacf6a5f49b1f15ae54481f7f3e4e69d859270e3a","first_computed_at":"2026-07-05T07:59:36.408285Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:59:36.408285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"auhUHDQa4pH0dD6r/Fr0ICyyZ6YC4muSVr9RIj7Xn0e5DTry7TfxlHlpEKBep2D9Z/TxEDrh9Oli9449RVTHAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:59:36.408774Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.14028","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3d49df4bb7123d40aa6ea55e8f268b891dcb5505f7c7092a7944b0740553411a","sha256:be18b7f727ec69b9478cdccacb3f2061512d78fa5d85832d83782bee49c0c1bc"],"state_sha256":"c169ddc866fee2b12349fc825ad0a88cddc5895e6aed788a4d8040d07f9bdadd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"p/B/KojWo3l9fyTREgb/uD+0Q6W1PtVlTHaQ7bBmtxY1/YvB563tO+S+EwJMPL6obw9MXHvkSUVVc1chGtZ3DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T20:56:26.741089Z","bundle_sha256":"91f1984c58940417220e608dbd4a3902b97c941121da865ae73840269b308529"}}