{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:X4DBNWXN6XRSPZLPASQP4GXLC2","short_pith_number":"pith:X4DBNWXN","canonical_record":{"source":{"id":"2009.11277","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-23T17:44:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e0dfa334ddcd54f6f244551986d3b3c6450ff8c08c8718638729c2911bf4d39a","abstract_canon_sha256":"d0256b323aed5e6801ec472473a6dabb9af904be632193d89f6cb01003b2ef58"},"schema_version":"1.0"},"canonical_sha256":"bf0616daedf5e327e56f04a0fe1aeb16990034fcd9032b7598b7861f00f3f845","source":{"kind":"arxiv","id":"2009.11277","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.11277","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"arxiv_version","alias_value":"2009.11277v1","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.11277","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"pith_short_12","alias_value":"X4DBNWXN6XRS","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"pith_short_16","alias_value":"X4DBNWXN6XRSPZLP","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"pith_short_8","alias_value":"X4DBNWXN","created_at":"2026-07-05T01:37:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:X4DBNWXN6XRSPZLPASQP4GXLC2","target":"record","payload":{"canonical_record":{"source":{"id":"2009.11277","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-23T17:44:07Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e0dfa334ddcd54f6f244551986d3b3c6450ff8c08c8718638729c2911bf4d39a","abstract_canon_sha256":"d0256b323aed5e6801ec472473a6dabb9af904be632193d89f6cb01003b2ef58"},"schema_version":"1.0"},"canonical_sha256":"bf0616daedf5e327e56f04a0fe1aeb16990034fcd9032b7598b7861f00f3f845","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:37:38.054667Z","signature_b64":"znN8v7dh/0Bv0zr3EJckNoiqOLpOr5d23TVROKCe3FbkE0djLZQT6i3ivZDUZrNhtHvIlWbVHsYX54HoiZpkBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bf0616daedf5e327e56f04a0fe1aeb16990034fcd9032b7598b7861f00f3f845","last_reissued_at":"2026-07-05T01:37:38.054241Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:37:38.054241Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2009.11277","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":"2026-07-05T01:37:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7QDu0EETP9Yebu/OMvyZA8KIL4HDD96ozkqoLgDOjC/TJmqn3123I4+Bykwcde7gNOaOcmGKYHovLBhRQxnoCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:58:29.573899Z"},"content_sha256":"aa55ee4c64f9619d231484a360286695ddc8ff2bf854be1783428ed613129dc8","schema_version":"1.0","event_id":"sha256:aa55ee4c64f9619d231484a360286695ddc8ff2bf854be1783428ed613129dc8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:X4DBNWXN6XRSPZLPASQP4GXLC2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Cunhua Pan, Kezhi Wang, Lajos Hanzo, Liang Wang, Nauman Aslam, Wei Xu","submitted_at":"2020-09-23T17:44:07Z","abstract_excerpt":"An unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) framework is proposed, where several UAVs having different trajectories fly over the target area and support the user equipments (UEs) on the ground. We aim to jointly optimize the geographical fairness among all the UEs, the fairness of each UAV' UE-load and the overall energy consumption of UEs. The above optimization problem includes both integer and continues variables and it is challenging to solve. To address the above problem, a multi-agent deep reinforcement learning based trajectory control algorithm is proposed for ma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.11277","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/2009.11277/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":"2026-07-05T01:37:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7xTvRvzyICKvpu7hPl+42g5f6cKTmvcxknEIEc6j7V9qU3n88hTXfLQCBQlCa5/Ki+V/tSHujveNWTH/OUTFCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:58:29.574407Z"},"content_sha256":"8ba2dd5e18ce6610976b2ea7f070cd94e4a82874966f19688a25cf0389c66562","schema_version":"1.0","event_id":"sha256:8ba2dd5e18ce6610976b2ea7f070cd94e4a82874966f19688a25cf0389c66562"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X4DBNWXN6XRSPZLPASQP4GXLC2/bundle.json","state_url":"https://pith.science/pith/X4DBNWXN6XRSPZLPASQP4GXLC2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X4DBNWXN6XRSPZLPASQP4GXLC2/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":"2026-08-04T23:58:29Z","links":{"resolver":"https://pith.science/pith/X4DBNWXN6XRSPZLPASQP4GXLC2","bundle":"https://pith.science/pith/X4DBNWXN6XRSPZLPASQP4GXLC2/bundle.json","state":"https://pith.science/pith/X4DBNWXN6XRSPZLPASQP4GXLC2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X4DBNWXN6XRSPZLPASQP4GXLC2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:X4DBNWXN6XRSPZLPASQP4GXLC2","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":"d0256b323aed5e6801ec472473a6dabb9af904be632193d89f6cb01003b2ef58","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-23T17:44:07Z","title_canon_sha256":"e0dfa334ddcd54f6f244551986d3b3c6450ff8c08c8718638729c2911bf4d39a"},"schema_version":"1.0","source":{"id":"2009.11277","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.11277","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"arxiv_version","alias_value":"2009.11277v1","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.11277","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"pith_short_12","alias_value":"X4DBNWXN6XRS","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"pith_short_16","alias_value":"X4DBNWXN6XRSPZLP","created_at":"2026-07-05T01:37:38Z"},{"alias_kind":"pith_short_8","alias_value":"X4DBNWXN","created_at":"2026-07-05T01:37:38Z"}],"graph_snapshots":[{"event_id":"sha256:8ba2dd5e18ce6610976b2ea7f070cd94e4a82874966f19688a25cf0389c66562","target":"graph","created_at":"2026-07-05T01:37:38Z","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/2009.11277/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"An unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) framework is proposed, where several UAVs having different trajectories fly over the target area and support the user equipments (UEs) on the ground. We aim to jointly optimize the geographical fairness among all the UEs, the fairness of each UAV' UE-load and the overall energy consumption of UEs. The above optimization problem includes both integer and continues variables and it is challenging to solve. To address the above problem, a multi-agent deep reinforcement learning based trajectory control algorithm is proposed for ma","authors_text":"Cunhua Pan, Kezhi Wang, Lajos Hanzo, Liang Wang, Nauman Aslam, Wei Xu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-23T17:44:07Z","title":"Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.11277","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:aa55ee4c64f9619d231484a360286695ddc8ff2bf854be1783428ed613129dc8","target":"record","created_at":"2026-07-05T01:37:38Z","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":"d0256b323aed5e6801ec472473a6dabb9af904be632193d89f6cb01003b2ef58","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2020-09-23T17:44:07Z","title_canon_sha256":"e0dfa334ddcd54f6f244551986d3b3c6450ff8c08c8718638729c2911bf4d39a"},"schema_version":"1.0","source":{"id":"2009.11277","kind":"arxiv","version":1}},"canonical_sha256":"bf0616daedf5e327e56f04a0fe1aeb16990034fcd9032b7598b7861f00f3f845","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bf0616daedf5e327e56f04a0fe1aeb16990034fcd9032b7598b7861f00f3f845","first_computed_at":"2026-07-05T01:37:38.054241Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:37:38.054241Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"znN8v7dh/0Bv0zr3EJckNoiqOLpOr5d23TVROKCe3FbkE0djLZQT6i3ivZDUZrNhtHvIlWbVHsYX54HoiZpkBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T01:37:38.054667Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.11277","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa55ee4c64f9619d231484a360286695ddc8ff2bf854be1783428ed613129dc8","sha256:8ba2dd5e18ce6610976b2ea7f070cd94e4a82874966f19688a25cf0389c66562"],"state_sha256":"3a1f1dde3cfa07d9014abd5e9789939f5db16c210afe6a085f10fbfb05783c65"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dX1Q1sV5+0OQcfw15G/VegfmRYaUlsO5dr+zoJvwDsjUGJXt+QpJdrrm8ySglOCI6MBqpQmbO8RYOvilb/YkBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T23:58:29.579502Z","bundle_sha256":"18bc28a00a0db6bc178414cb638387771d21b0e125b1226eaee250c48f36c81e"}}