Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:34:11.246739Z
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2505.06997.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:34:11.246739Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
48 of 48 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8bdb5e27-83f8-4b5b-a7b3-3b9c47e0fc8b · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue A comprehensive survey on mobile crowdsensing systems,
Reference 1
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 97a6eb59-3122-4f22-b9b0-1f4560b6be91 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Privacy-preserving mechanisms for location privacy in mobile crowdsensing: A survey,
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0d16cf28-c918-4366-a53e-d6c046fcd4df · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Drift: A dynamic crowd inflow control system using lstm-based deep reinforcement learn- ing,
Reference 3
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 68526008-232a-4722-8931-d4840a48b9e5 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue A survey on task assignment in crowdsourcing,
Reference 4
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d41f8c1d-de4b-4c60-9d1d-596494d0d0df · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Towards crowd- sourcing internet of things (crowd-iot): Architectures, security and applications,
Reference 5
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation aa782874-42f2-4fdc-8dcf-1614d65a5b86 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Task-oriented wireless communications for collaborative perception in intelligent un- manned systems,
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0657766f-1b05-483f-9a1e-166e060b58f9 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Unified perception and collaborative mapping for connected and autonomous vehicles,
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation be83b62f-7765-4a4e-aee2-b2824b806fa2 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue A survey and framework of cooperative perception: From heterogeneous singleton to hierarchical cooperation,
Reference 8
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6ed7528c-fa91-47c7-ac9a-3c340fc4a1f1 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Air-ground spatial crowdsourcing with uav carriers by geometric graph convolutional multi-agent deep reinforcement learning,
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 355c9d3f-9ecd-4e94-a8a6-9d8d7b111db9 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Energy-efficient ground-air-space vehicular crowdsensing by hierarchical multi-agent deep reinforcement learning with diffusion models,
Reference 10
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c4b17752-71a7-445f-aca0-8fe360c7fe17 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue The system framework and application research of the parallel emergency management system (pems),
Reference 11
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation c9f52503-2851-424e-93dd-2020741bf394 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Parallel emergency management of incidents by integrating ooda and prea loops: The c2 mechanism and modes,
Reference 12
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4c3ad42a-a6d3-494b-92a5-c90e007588d7 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Towards time- constrained task allocation in semi-opportunistic mobile crowdsensing,
Reference 13
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6bc3529b-8e7c-4e5f-8b84-e1f362eee168 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Optimal resource allocation for uav-relay-assisted mobile crowdsensing,
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8b145712-b9ab-4b29-8e11-120ef19ea565 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Mappo-based cooperative uav trajectory design with long-range emergency communications in disaster areas,
Reference 15
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation af6355f3-301b-4223-82e3-3982b4d360e1 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Disaster-resilient emergency communication with intelligent air–ground cooperation,
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation f80745fc-aa35-44ec-900f-81ac3a9e7b0d · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Task search and alloca- tion strategy for heterogeneous multiagent systems under communication constraints,
Reference 17
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0f61cc80-ab7c-4917-a37a-a33551fb6cc6 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Cooperative multi- aav path planning for discovering and tracking multiple radio-tagged targets,
Reference 18
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 73ea8c17-6836-407a-a599-6829bd17211c · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Robust training in multiagent deep reinforcement learning against optimal adversary,
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d35a4077-fe0b-4adf-be4c-cad4775a3ee7 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Sensors on the internet of things systems for urban disaster management: a systematic literature review,
Reference 20
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation eec004b5-6693-403f-92b4-9c24fff61d1c · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Optimization of emergency rescue routes after a violent earthquake,
Reference 21
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 784d75c3-0f6d-4ef1-bc50-61a8c11a51b6 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Autonomous unmanned aerial vehicles in bushfire management: Challenges and opportunities,
Reference 22
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 230b68b7-45ac-49ef-919f-7f507ed45c39 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Gacf: Ground-aerial collaborative framework for large-scale emergency rescue scenarios,
Reference 23
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 185431d8-7017-4a18-8fe3-7d6f88224e8a · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Cooperative unmanned surface vehicles and unmanned aerial vehicles platform as a tool for coastal monitoring activities,
Reference 24
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 102980b2-a80e-49a9-bd49-2c9289046c02 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Human detection and action recognition for search and rescue in disasters using yolov3 algorithm,
Reference 25
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5aa24dc5-6dde-44e1-9630-6c2ac0a3a0c9 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue A comprehensive survey of unmanned ground vehicle terrain traversability for unstructured environments and sensor technology insights,
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation de2c5cbb-9b6d-40ff-b533-8a2664769983 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Unmanned aerial vehicles for search and rescue: A survey,
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 29d4f407-b407-4858-8d1b-7a4a269d5435 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue A crowd- aided vehicular hybrid sensing framework for intelligent transportation systems,
Reference 28
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 739228ff-6d2b-441d-80ca-51b294950f55 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Cooperative uav trajectory design for disaster area emergency communications: A multiagent ppo method,
Reference 29
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 2e460a60-32ea-47f1-bb63-032329f823c2 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Collab- orative route planning of uavs, workers, and cars for crowdsensing in disaster response,
Reference 30
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 14deaee0-dcdf-4472-87e3-5494b1a4065f · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Decentralized task assignment for mobile crowd- sensing with multi-agent deep reinforcement learning,
Reference 31
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7db605fd-9f07-4c47-88ec-19f87e00a7d6 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Ensuring threshold aoi for uav-assisted mobile crowdsensing by multi-agent deep reinforcement learning with transformer,
Reference 32
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation be67d6dd-e7f4-474b-8284-76d98dac80a8 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Exploring both individuality and cooperation for air-ground spatial 16 crowdsourcing by multi-agent deep reinforcement learning,
Reference 33
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation de0dcba2-31bf-4b6e-9da1-d3330cbfc96b · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Heterogeneous Graph Reinforcement Learning for Dependency-aware Multi-task Allocation in Spatial Crowdsourcing
Reference 34
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 7f70d911-2e1c-49c8-947f-4d7bbad160a9 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Energy-efficient 3d vehicular crowdsourcing for disaster response by distributed deep reinforcement learning,
Reference 35
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 5f96448a-ec90-4533-85d3-35c06857fba1 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Pomdp inference and robust solution via deep reinforce- ment learning: An application to railway optimal maintenance,
Reference 36
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8d21c0e2-0956-4bbb-b19a-a6928881da6f · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Informed POMDP: Leveraging Additional Information in Model-Based RL
Reference 37
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 24b9feae-ceb0-4fab-b543-bfdb6865213c · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue An effective cnn and transformer com- plementary network for medical image segmentation,
Reference 38
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 065b02a1-ff00-4a84-ae26-5c9db53939b3 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue A comprehensive overview and comparative analysis on deep learning models,
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 14b5a24a-cb95-4c3c-9211-ae08216c2c98 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning
Reference 40
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation abf7f1ef-b04c-4c9f-b754-7548a4f24956 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Intelligent routing method based on dueling dqn reinforcement learning and net- work traffic state prediction in sdn,
Reference 41
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 4bf4a882-a407-4422-a2e6-4dcca883e63b · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Monotonic value function factorisation for deep multi- agent reinforcement learning,
Reference 42
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 72ea18b5-b7fb-4cde-95e7-3a6569d88936 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Qtran: Learning to factorize with transformation for cooperative multi-agent reinforcement learning,
Reference 43
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation cd907e37-d861-42c5-8a28-7e993a6df660 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue The surprising effectiveness of ppo in cooperative multi-agent games,
Reference 44
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0bf045bb-f017-4f96-9e06-776f0d749e02 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Online organizing large-scale heterogeneous tasks and multi-skilled participants in mobile crowdsensing,
Reference 45
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation d61abab3-4df8-4390-99ff-9d332291c285 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Human-drone collaborative spatial crowdsourcing by memory- augmented and distributed multi-agent deep reinforcement learning,
Reference 46
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 841ef362-09a8-4935-bfe3-4fa4ffc7d826 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue Modeling human steering behavior in teleoperation of unmanned ground vehicles with varying speed,
Reference 47
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 6dfa1901-079b-4c0a-aa62-1a07a21fc967 · outbound
A Multi-Agent Reinforcement Learning Approach for Cooperative Air-Ground-Human Crowdsensing in Emergency Rescue 3d building model generation from mls point cloud and 3d mesh using multi-source data fusion,
Reference 48
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
No inbound Pith citation observations are available.