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Paper Citation Record · LEDGER

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning

As of 19 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2510.03534.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2510.03534 v5

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:41:10.810438Z

measured 32 of 32 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

32 of 32 outbound references displayed

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Outbound references

Observation 0e8cf4d8-1593-4b5e-9360-d312d9f24b49 · outbound

This paper cites AI-Driven Marine Robotics: Emerging Trends in Underwater Perception and Ecosystem Monitoring.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning AI-Driven Marine Robotics: Emerging Trends in Underwater Perception and Ecosystem Monitoring

Reference 1

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Observation 56ba59ea-3245-40ae-ac48-67f4a7604ebd · outbound

This paper cites The use of emerging autonomous technologies for ocean monitoring: insights and legal challenges,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning The use of emerging autonomous technologies for ocean monitoring: insights and legal challenges,

Reference 2

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Observation 49da82f3-0901-44c1-bb8f-da21a014cf53 · outbound

This paper cites Observation of a turbid plume using modis imagery: The case of douro estuary (portugal),.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Observation of a turbid plume using modis imagery: The case of douro estuary (portugal),

Reference 3

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Observation 09a5606c-fa2f-4d2d-aead-881fe8b8dc45 · outbound

This paper cites Mixing and transport in coastal river plumes,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Mixing and transport in coastal river plumes,

Reference 4

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source=pdf_text observed=2026-08-04T11:41:07.743328Z digest=sha256:df49ab1f80ea1336d4a7e491503551a457963a175f75249bc1ad15a7cb290ca2

Observation d6295695-77a2-45e4-9fc7-eba29c4b5665 · outbound

This paper cites 3D Tracking of a River Plume Front with an AUV,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning 3D Tracking of a River Plume Front with an AUV,

Reference 5

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Observation 29bedb88-3c59-4310-895b-96c78d81a9a5 · outbound

This paper cites Formation control of multiple autonomous underwater vehicles: a review,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Formation control of multiple autonomous underwater vehicles: a review,

Reference 6

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source=pdf_text observed=2026-08-04T11:41:07.968458Z digest=sha256:971bc6b26ecdf2b0fb30d7712e6291bdce494e27ea9cb36c1fd0e071afe07123

Observation 84338348-5d2c-4499-8c51-a6885b30a3d2 · outbound

This paper cites The douro estuary (portugal): a mesotidal salt wedge,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning The douro estuary (portugal): a mesotidal salt wedge,

Reference 7

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Observation d89d4f21-80ed-470e-88c3-0b89b393b56a · outbound

This paper cites Drivers of spatio-temporal patterns of salinity in spanish rivers: a nationwide assessment,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Drivers of spatio-temporal patterns of salinity in spanish rivers: a nationwide assessment,

Reference 8

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Observation 5a7fed43-d28f-405e-acad-053527f0400a · outbound

This paper cites Characterization of river plume dynamics for a better water quality management,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Characterization of river plume dynamics for a better water quality management,

Reference 9

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source=pdf_text observed=2026-08-04T11:41:08.335707Z digest=sha256:135116bb5dbb1835651e99e7446e2cfc23d100e3b9c71b69d49edca4dbf3c492

Observation 3dc8b70b-2270-4347-b05c-96b0777d5bd8 · outbound

This paper cites Validation Document Delft3D-FLOW; a software system for 3D flow simulations,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Validation Document Delft3D-FLOW; a software system for 3D flow simulations,

Reference 10

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Observation 570fc97b-e881-4baa-adcc-14c8e950fb1f · outbound

This paper cites Integrated high-resolution numerical model for the nw iberian peninsula coast and main estuarine systems,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Integrated high-resolution numerical model for the nw iberian peninsula coast and main estuarine systems,

Reference 11

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Observation 2b3afde0-7996-40e9-a60b-b3d87b4192c2 · outbound

This paper cites Two-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Two-dimensional mapping and tracking of a coastal upwelling front by an autonomous underwater vehicle,

Reference 12

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Observation 1c576036-142f-41cf-902b-eeeabbf1d9f2 · outbound

This paper cites AUV Adaptive Sampling Methods: A Review,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning AUV Adaptive Sampling Methods: A Review,

Reference 13

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source=pdf_text observed=2026-08-04T11:41:08.844070Z digest=sha256:42c9663b028a3ea99a7e538fe6ecdd5453316ec324f21dc31069a54f8a02c9e9

Observation 600bb992-97ad-4745-ac95-bb0d8d1db81e · outbound

This paper cites Hierarchical probabilistic regression for auv-based adaptive sampling of marine phenomena,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Hierarchical probabilistic regression for auv-based adaptive sampling of marine phenomena,

Reference 14

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Observation 3096daed-0f43-48af-b123-a0ae65603482 · outbound

This paper cites Sampling-based robotic information gathering algorithms,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Sampling-based robotic information gathering algorithms,

Reference 15

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source=pdf_text observed=2026-08-04T11:41:09.138126Z digest=sha256:22bf620c08893933e644e128a7990928e769daabf44ac360e0a6e88db689c762

Observation cb3e47b1-c210-44ca-be45-187944f1e334 · outbound

This paper cites Informative path planning in random fields via mixed integer programming,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Informative path planning in random fields via mixed integer programming,

Reference 16

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Observation 0b816e03-ad04-409b-9290-f0f617d04008 · outbound

This paper cites 3-D adaptive AUV sam- pling for classification of water masses,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning 3-D adaptive AUV sam- pling for classification of water masses,

Reference 17

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Observation 1e472c8d-0c7e-4a95-81bf-ffbbd8c935b8 · outbound

This paper cites Efficient 3d real-time adaptive auv sampling of a river plume front,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Efficient 3d real-time adaptive auv sampling of a river plume front,

Reference 18

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Observation 2cdd6e6e-466a-495c-bab1-a5be9699e871 · outbound

This paper cites A multiagent deep reinforcement learning approach for path planning in autonomous surface vehicles: The Ypacara ´ı lake patrolling case,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning A multiagent deep reinforcement learning approach for path planning in autonomous surface vehicles: The Ypacara ´ı lake patrolling case,

Reference 19

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Observation 1235a795-1cfa-461a-a36f-e5ab11aebd1c · outbound

This paper cites Adaptive path planning using Gaussian process regression: a reinforcement learning approach,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Adaptive path planning using Gaussian process regression: a reinforcement learning approach,

Reference 20

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Observation d551800c-f2a6-4182-ae8d-0b546da699ef · outbound

This paper cites Cooperative deep reinforcement learning for dynamic pollution plume monitoring using a drone fleet,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Cooperative deep reinforcement learning for dynamic pollution plume monitoring using a drone fleet,

Reference 21

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Observation c132b4b4-e031-4372-a9ae-781fafe9efee · outbound

This paper cites Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Deep Learning Based Active Spatial Channel Gain Prediction Using a Swarm of Unmanned Aerial Vehicles

Reference 22

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Observation 47aab580-e70c-43eb-9899-45d2a39dcc8d · outbound

This paper cites Wildfire front monitoring with multiple uavs using deep q-learning,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Wildfire front monitoring with multiple uavs using deep q-learning,

Reference 23

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Observation 66269f6e-752e-4d30-8efb-416e5e0a5a62 · outbound

This paper cites Trajectory optimization for underwater vehi- cles in time-varying ocean flows,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Trajectory optimization for underwater vehi- cles in time-varying ocean flows,

Reference 24

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Observation bfa49173-ad88-4242-b514-5bdf28ff02e9 · outbound

This paper cites Errors in dynamical fields inferred from oceanographic cruise data: Part II. The impact of the lack of synopticity,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Errors in dynamical fields inferred from oceanographic cruise data: Part II. The impact of the lack of synopticity,

Reference 25

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Observation f096cb01-ddc9-4bac-85ce-2376985e4c0d · outbound

This paper cites Carlton, Marine propellers and propulsion.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Carlton, Marine propellers and propulsion

Reference 26

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Observation 297e3137-415c-41ae-b18e-cb2ae52e2431 · outbound

This paper cites an unresolved cited work.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Unresolved cited work

Reference 27

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Observation 7d3061f0-e4fc-44ac-8726-6c352680a451 · outbound

This paper cites Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning

Reference 28

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Observation 561f07f9-6c18-41fd-876d-0f85b6da2a63 · outbound

This paper cites Grandmaster level in StarCraft II using multi-agent reinforcement learning,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Grandmaster level in StarCraft II using multi-agent reinforcement learning,

Reference 29

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Observation eba46139-a602-4c81-8ced-00df408c0014 · outbound

This paper cites Distributed multi-agent target search and tracking with gaussian process and reinforcement learning,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Distributed multi-agent target search and tracking with gaussian process and reinforcement learning,

Reference 30

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Observation f687dae9-2399-4dee-8ff9-758a41094519 · outbound

This paper cites Credit assignment for collective multiagent RL with global rewards,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Credit assignment for collective multiagent RL with global rewards,

Reference 31

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source=pdf_text observed=2026-08-04T11:41:10.710706Z digest=sha256:260efdea95c37ec17017389cfaae1881729844e4a8a7e9c80e9b4baa0e2537c1

Observation 2a2c0995-b7ed-4399-8acd-c8ca25248b3a · outbound

This paper cites Dis- tributed coverage control for time-varying spatial processes,.

Long-Term Mapping of the Douro River Plume with Multi-Agent Reinforcement Learning Dis- tributed coverage control for time-varying spatial processes,

Reference 32

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