Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning | Paper Citation Record

Observation 6e0d9c77-6495-4e38-84cf-7fc93a10d53c · outbound

This paper cites Benefits of Advanced Air Mobility for Society and Environment: A Case Study of Ohio,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Benefits of Advanced Air Mobility for Society and Environment: A Case Study of Ohio,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.107988Z

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Observation 1598afd4-19bd-43d0-9ad5-72a1c3b95444 · outbound

This paper cites Infrastructure To Support Advanced Autonomous Aircraft Technologies in Ohio: Economic Impact Report for Advanced Autonomous Aircraft Technologies in Ohio,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Infrastructure To Support Advanced Autonomous Aircraft Technologies in Ohio: Economic Impact Report for Advanced Autonomous Aircraft Technologies in Ohio,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.147175Z

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Observation f231f4e7-ba87-450d-95b3-b8706c0de072 · outbound

This paper cites Open Framework Standards for Combined Aircraft Sensor Network for the State of Ohio to Detect and Track Lower Altitude Aircraft: Cost-Benefit Analysis,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Open Framework Standards for Combined Aircraft Sensor Network for the State of Ohio to Detect and Track Lower Altitude Aircraft: Cost-Benefit Analysis,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.226653Z

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Observation c36cf454-0899-4632-a759-0059a7ae7a37 · outbound

This paper cites Open Framework Standards for Combined Aircraft Sensor Network for the State of Ohio to Detect and Track Lower Altitude Aircraft,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Open Framework Standards for Combined Aircraft Sensor Network for the State of Ohio to Detect and Track Lower Altitude Aircraft,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.320491Z

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Observation 2fb83500-08a5-4e20-af60-1ba4681c0656 · outbound

This paper cites Concept of Operations v2.0, Unmanned aircraft System (UAS) Traffic Management (UTM),.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Concept of Operations v2.0, Unmanned aircraft System (UAS) Traffic Management (UTM),

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.398419Z

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Observation 87f4958f-e370-4285-a7e8-98500ff04814 · outbound

This paper cites Urban air mobility (UAM) market study,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Urban air mobility (UAM) market study,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.479390Z

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Observation 5ef66e4e-1a94-4738-a462-d3823cf3b862 · outbound

This paper cites Building Public–Private Partnerships for Advanced Air Mobility Infrastructure Using Game Theory,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Building Public–Private Partnerships for Advanced Air Mobility Infrastructure Using Game Theory,

Reference 7

Resolution: verified exact; doi, observed 2026-08-02T06:48:24.436879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1359cc5a-1328-452e-b204-db48ef339b38 · outbound

This paper cites How to Negotiate with Private Investors for Advanced Air Mobility Infrastructure? An Analysis of Public Private Partnerships Using Game Theory,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning How to Negotiate with Private Investors for Advanced Air Mobility Infrastructure? An Analysis of Public Private Partnerships Using Game Theory,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.671925Z

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Observation 8457da52-7601-4b33-bb88-fd3dcfec33a8 · outbound

This paper cites Low-Noise Route and Operations Planning for Food Delivery UnmannedAerialVehicles,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Low-Noise Route and Operations Planning for Food Delivery UnmannedAerialVehicles,

Reference 9

Resolution: verified exact; doi, observed 2026-08-02T06:48:24.252258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 462d3cb6-dda5-4615-adeb-b0ff6648224b · outbound

This paper cites Dynamic Dispatching of Package Delivery UAVs Considering Safety Risk and Noise and Visual Pollution,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Dynamic Dispatching of Package Delivery UAVs Considering Safety Risk and Noise and Visual Pollution,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.846301Z

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Observation c83fe7db-1254-47f9-ac4a-64252ef5442a · outbound

This paper cites An integrated supply chain network design for advanced air mobility aircraft manufacturing using stochastic optimization,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning An integrated supply chain network design for advanced air mobility aircraft manufacturing using stochastic optimization,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.924001Z

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Observation fc18cf1a-56f4-41ba-9f43-1e65606a7c0c · outbound

This paper cites Urban Air Mobility Concept of Operations, Version 2.0,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Urban Air Mobility Concept of Operations, Version 2.0,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:33.986993Z

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Observation 574f5bcb-e6db-417c-b6dc-5c3d274fb0ff · outbound

This paper cites Reliable, Secure, and Scalable Communications,Navigation,andSurveillanceOptionsforUrbanAirMobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Reliable, Secure, and Scalable Communications,Navigation,andSurveillanceOptionsforUrbanAirMobility,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.059192Z

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Observation 6c6cd56f-f851-4aae-8082-9a8b5739f120 · outbound

This paper cites Next-Generation Airborne Collision Avoidance System,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Next-Generation Airborne Collision Avoidance System,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.143289Z

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Observation 92018e53-f580-4592-baf1-bc72345605be · outbound

This paper cites Designing a Surveillance Sensor Network with Information Clearinghouse for Advanced Air Mobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Designing a Surveillance Sensor Network with Information Clearinghouse for Advanced Air Mobility,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.230949Z

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Observation b4f5c02f-4cc9-4f5a-96c2-0061ca6f8e2b · outbound

This paper cites Reliability, Robustness, and Resilience Modeling for Surveillance Systems in Advanced Air Mobility Operations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Reliability, Robustness, and Resilience Modeling for Surveillance Systems in Advanced Air Mobility Operations,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.284544Z

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Observation 110cc33a-9a5f-48b9-bbb8-7be8fb1909b6 · outbound

This paper cites A Survey of Recent Results in Networked Control Systems,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning A Survey of Recent Results in Networked Control Systems,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.369216Z

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Observation fbf6df02-241e-4d83-85a2-42c35237b675 · outbound

This paper cites Kalman Filtering with Intermittent Observations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Kalman Filtering with Intermittent Observations,

Reference 18

Resolution: malformed identifier; no resolver link, observed 2026-08-02T06:47:34.424074Z

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Observation fccaa2cf-bea5-4ae9-ad09-61dbcf97eba5 · outbound

This paper cites Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.506019Z

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Observation b90d9918-8230-414e-bcef-ff272de61f62 · outbound

This paper cites Reinforcement Learning with Delayed Observations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Reinforcement Learning with Delayed Observations,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.568973Z

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Observation dccfd156-98dc-4ed2-aab5-183126f0daa6 · outbound

This paper cites Urban Air Mobility Airspace Integration Concepts and Considerations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Urban Air Mobility Airspace Integration Concepts and Considerations,

Reference 21

Resolution: verified exact; doi, observed 2026-08-02T06:48:24.078085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e5e0ac06-8ff7-4fb5-a016-6d08d7f5a000 · outbound

This paper cites Designing Airspace for Urban Air Mobility: A Review of Concepts and Approaches,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Designing Airspace for Urban Air Mobility: A Review of Concepts and Approaches,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.702807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d392fa8-1063-4bca-bdba-c9b3d19ec76d · outbound

This paper cites A Review of Conflict Detection and Resolution Modeling Methods,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning A Review of Conflict Detection and Resolution Modeling Methods,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.760427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b37c940c-6fbb-4eb4-8df6-57110077fd29 · outbound

This paper cites A Multi-Agent Reinforcement Learning Approach for Conflict Resolution in Dense Traffic Scenarios,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning A Multi-Agent Reinforcement Learning Approach for Conflict Resolution in Dense Traffic Scenarios,

Reference 24

Resolution: malformed identifier; no resolver link, observed 2026-08-02T06:47:34.809088Z

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Observation 7eb23942-ac46-4209-bd88-a70fa87bf488 · outbound

This paper cites Autonomous Separation Assurance with Deep Multi-Agent Reinforcement Learning,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Autonomous Separation Assurance with Deep Multi-Agent Reinforcement Learning,

Reference 25

Resolution: verified exact; doi, observed 2026-08-02T06:48:23.870409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5dda025-ec38-4a38-97f9-28e5ecfea31a · outbound

This paper cites Motion Planning in Dynamic Environments Using Velocity Obstacles,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Motion Planning in Dynamic Environments Using Velocity Obstacles,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:34.949058Z

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Observation 2398693f-78d4-4fdb-8254-6267eef62cd5 · outbound

This paper cites Conflict-FreeFour-DimensionalPathPlanningforUrbanAirMobilityConsideringAirspace Occupancy,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Conflict-FreeFour-DimensionalPathPlanningforUrbanAirMobilityConsideringAirspace Occupancy,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.006261Z

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Observation fcc39e12-cb6b-4f0e-8ed0-89211a04db50 · outbound

This paper cites Automated Flight Planning of High-Density Urban Air Mobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Automated Flight Planning of High-Density Urban Air Mobility,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.057154Z

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Unavailable: canonical work link unavailable.

Observation fdede2f3-3f8c-4cae-a79e-fca257bfd410 · outbound

This paper cites Human-Level Control through Deep Reinforcement Learning,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Human-Level Control through Deep Reinforcement Learning,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.107059Z

Source-reported events for the cited work

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Observation b9274cfc-b6e0-4142-b14a-a8af1d89ebc4 · outbound

This paper cites Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.162165Z

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Observation df89a5e4-2232-420a-a6a7-97013898b494 · outbound

This paper cites One to Any: Distributed Conflict Resolution with Deep Multi-Agent Reinforcement Learning,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning One to Any: Distributed Conflict Resolution with Deep Multi-Agent Reinforcement Learning,

Reference 31

Resolution: malformed identifier; no resolver link, observed 2026-08-02T06:47:35.236872Z

Source-reported events for the cited work

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Observation 562c2ea5-e83e-4fa6-a7d6-3f4a1cb949ff · outbound

This paper cites Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Multi-UAV Conflict Resolution with Graph Convolutional Reinforcement Learning,

Reference 32

Resolution: verified exact; doi, observed 2026-08-02T06:48:23.688824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7a2d02b9-356b-4f5e-942e-f2df9d10802b · outbound

This paper cites Strategic Conflict Management Using Recurrent Multi-Agent Reinforcement Learning for Urban Air Mobility Operations Considering Uncertainties,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Strategic Conflict Management Using Recurrent Multi-Agent Reinforcement Learning for Urban Air Mobility Operations Considering Uncertainties,

Reference 33

Resolution: verified exact; doi, observed 2026-08-02T06:48:23.477188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7837555f-e54a-42be-bb4d-f7a414c75d0e · outbound

This paper cites Autonomous Conflict Resolution in Urban Air Mobility: A Deep Multi-Agent Reinforcement Learning Approach,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Autonomous Conflict Resolution in Urban Air Mobility: A Deep Multi-Agent Reinforcement Learning Approach,

Reference 34

Resolution: verified exact; doi, observed 2026-08-02T06:48:23.311322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8db40ec5-1d22-4ac8-ac34-821b71a289f4 · outbound

This paper cites AReinforcementLearningApproachtoVehicleCoordinationforStructuredAdvanced Air Mobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning AReinforcementLearningApproachtoVehicleCoordinationforStructuredAdvanced Air Mobility,

Reference 35

Resolution: verified exact; doi, observed 2026-08-02T06:48:23.065722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ea3a7a0f-b56f-4863-b35b-5371eb8c9f64 · outbound

This paper cites Self-Organized Free-Flight Arrival for Urban Air Mobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Self-Organized Free-Flight Arrival for Urban Air Mobility,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.633215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca827a8b-ce39-4cfb-a209-b4086fee0655 · outbound

This paper cites Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic,

Reference 37

Resolution: verified exact; doi, observed 2026-08-02T06:48:22.816619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 10192044-7235-4cce-a786-bb27f37c6a3f · outbound

This paper cites Air Traffic Assignment for Intensive Urban Air Mobility Operations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Air Traffic Assignment for Intensive Urban Air Mobility Operations,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.791081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26e58765-7449-476a-ae7a-0903a0c11ea4 · outbound

This paper cites Safe and Scalable Real-Time Trajectory Planning Framework for Urban Air Mobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Safe and Scalable Real-Time Trajectory Planning Framework for Urban Air Mobility,

Reference 39

Resolution: verified exact; doi, observed 2026-08-02T06:48:22.463207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c34e569a-7370-4516-823c-efb641817c97 · outbound

This paper cites Reinforcement Learning with Random Delays,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Reinforcement Learning with Random Delays,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:35.925166Z

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Observation d5f4bfa6-1a8c-4128-84f0-5dca49b3ee02 · outbound

This paper cites Probabilistic Modeling and Reasoning of Conflict Detection Effectiveness by Tracking Systems Towards Safe Urban Air Mobility Operations,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Probabilistic Modeling and Reasoning of Conflict Detection Effectiveness by Tracking Systems Towards Safe Urban Air Mobility Operations,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:36.004251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bf7e0fd-4be6-4201-961e-00faf7cf3508 · outbound

This paper cites Modeling Power Consumptions for Multirotor UAVs,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Modeling Power Consumptions for Multirotor UAVs,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:36.082226Z

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Observation 53213646-3bd9-4923-a9af-08a05393e954 · outbound

This paper cites Data-Efficient Modeling for Precise Power Consumption Estimation of Quadrotor Operations Using Ensemble Learning.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Data-Efficient Modeling for Precise Power Consumption Estimation of Quadrotor Operations Using Ensemble Learning

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:36.166435Z

Source-reported events for the cited work

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Observation 6001e573-ac3e-4239-bf26-a1f51dec69d2 · outbound

This paper cites Energy-Efficient Arrival with RTA Constraint for Multirotor eVTOL in Urban Air Mobility,.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Energy-Efficient Arrival with RTA Constraint for Multirotor eVTOL in Urban Air Mobility,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-02T06:47:36.251715Z

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