Paper Citation Record · LEDGER

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning

As of 12 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2603.24238.

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

pith.paper-citation-record.v1
2603.24238 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T19:00:18.283733Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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verified fuzzy0
unresolved36
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External citation measurements

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Outbound references

Observation 28e532ef-5b85-4a2d-a8a6-2594b32971f5 · outbound

This paper cites Racer: Rapid collaborative exploration with a decentralized multi-uav system,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Racer: Rapid collaborative exploration with a decentralized multi-uav system,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 92d213e3-5340-4bad-ae79-524e72428ab5 · outbound

This paper cites Swarm of micro flying robots in the wild,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Swarm of micro flying robots in the wild,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 0124c68c-d310-4f7e-8c7e-ff9ccda3c56e · outbound

This paper cites Proximal cooperative aerial manipulation with vertically stacked drones,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Proximal cooperative aerial manipulation with vertically stacked drones,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 31867f57-8531-4231-afc2-0e1060f4734c · outbound

This paper cites Primitive-swarm: An ultra-lightweight and scalable planner for large- scale aerial swarms,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Primitive-swarm: An ultra-lightweight and scalable planner for large- scale aerial swarms,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation a0ad52c3-5aee-4268-8285-912950357232 · outbound

This paper cites Search and pursuit-evasion in mobile robotics: A survey,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Search and pursuit-evasion in mobile robotics: A survey,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation a6e21423-fe82-45fd-a66b-099ce6c2b8fb · outbound

This paper cites Isaacs,Differential games: a mathematical theory with applications to warfare and pursuit, control and optimization.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Isaacs,Differential games: a mathematical theory with applications to warfare and pursuit, control and optimization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 51c3a704-59ba-4dd0-8d62-f62cad3c0edd · outbound

This paper cites Proba- bilistic pursuit-evasion games: theory, implementation, and experimental evaluation,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Proba- bilistic pursuit-evasion games: theory, implementation, and experimental evaluation,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 592fc8dd-40eb-49e4-8996-21684b6f0d5e · outbound

This paper cites Multi-robot cooperative pursuit via potential field-enhanced reinforcement learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Multi-robot cooperative pursuit via potential field-enhanced reinforcement learning,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation e2c36b15-f868-4005-b502-b337dfa3bc04 · outbound

This paper cites Online planning for multi-uav pursuit-evasion in unknown environments using deep reinforcement learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Online planning for multi-uav pursuit-evasion in unknown environments using deep reinforcement learning,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation aff1ebba-81fe-4070-a8f7-5673f1d87ca7 · outbound

This paper cites Game of drones: Intelligent online decision making of multi-uav confrontation,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Game of drones: Intelligent online decision making of multi-uav confrontation,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 26944f73-a8b5-4342-a9c1-6f41abdf1e18 · outbound

This paper cites Pursuit-evasion game strategy of usv based on deep reinforcement learning in complex multi-obstacle environment,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Pursuit-evasion game strategy of usv based on deep reinforcement learning in complex multi-obstacle environment,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 976f88af-c487-4698-985f-11b8e9532434 · outbound

This paper cites Champion-level drone racing using deep reinforcement learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Champion-level drone racing using deep reinforcement learning,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 153175b0-ed37-46ba-b7ee-505e7112e25b · outbound

This paper cites Navrl: Learning safe flight in dynamic environments,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Navrl: Learning safe flight in dynamic environments,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 74aa5ea2-ed33-46c8-9125-a459248da17c · outbound

This paper cites You only plan once: A learning-based one-stage planner with guidance learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning You only plan once: A learning-based one-stage planner with guidance learning,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation ff052a49-290d-4c55-aa55-62666ee755ac · outbound

This paper cites Learning vision-based agile flight via differentiable physics,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Learning vision-based agile flight via differentiable physics,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation cfca80a2-86c1-4b6f-9567-ffe4026a7579 · outbound

This paper cites Omnidrones: An efficient and flexible platform for reinforcement learning in drone control,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Omnidrones: An efficient and flexible platform for reinforcement learning in drone control,

Reference 16

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Observation 993014d4-5339-42f9-9cc8-e81bafc7b25e · outbound

This paper cites Distributed pursuit of an evader with collision and obstacle avoidance,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Distributed pursuit of an evader with collision and obstacle avoidance,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 0057f7ee-102e-4611-ad8e-7453bd30450b · outbound

This paper cites Intercepting rogue robots: An algorithm for capturing multiple evaders with multiple pursuers,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Intercepting rogue robots: An algorithm for capturing multiple evaders with multiple pursuers,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 87c1dd79-cb5c-4ae1-bdb2-18e9a8f92364 · outbound

This paper cites Real-time obstacle avoidance for manipulators and mobile robots,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Real-time obstacle avoidance for manipulators and mobile robots,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation c2057439-e968-4fb8-a580-42d7cc613a89 · outbound

This paper cites Collective predation and escape strategies,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Collective predation and escape strategies,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation b165a68f-8786-4ce3-b979-7be7e37fd529 · outbound

This paper cites Group chasing tactics: how to catch a faster prey,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Group chasing tactics: how to catch a faster prey,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

Source-reported events for the cited work

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Observation 4ee277d3-931a-4770-935d-50b6823347d5 · outbound

This paper cites Potential field methods and their inherent limitations for mobile robot navigation.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Potential field methods and their inherent limitations for mobile robot navigation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 08b6a795-1a6f-4333-a122-f23ea12be7fc · outbound

This paper cites Decentralized multi-agent pursuit using deep reinforcement learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Decentralized multi-agent pursuit using deep reinforcement learning,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 6a2253b4-8faa-4e8d-8017-1b3a2f5e2df9 · outbound

This paper cites Cooperative control for multi-player pursuit-evasion games with reinforcement learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Cooperative control for multi-player pursuit-evasion games with reinforcement learning,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation a1e4eb86-0dfd-4c1f-8275-03e3662344a4 · outbound

This paper cites Cooperative multi-agent control using deep reinforcement learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Cooperative multi-agent control using deep reinforcement learning,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 4b050478-9c02-4f05-8ce0-169c63e6e325 · outbound

This paper cites The complexity of decentralized control of markov decision processes,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning The complexity of decentralized control of markov decision processes,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 7aa15668-7e03-4951-89f0-a67ec30889da · outbound

This paper cites Agile in the face of delay: Asynchronous end-to-end learning for real-world aerial navigation,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Agile in the face of delay: Asynchronous end-to-end learning for real-world aerial navigation,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 9c088df1-34a3-43cb-8070-f7fa8a85686d · outbound

This paper cites What the constant velocity model can teach us about pedestrian motion prediction,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning What the constant velocity model can teach us about pedestrian motion prediction,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 958883eb-734f-46b7-8538-0f2139b4e907 · outbound

This paper cites Multi-scale context aggregation by dilated convolutions,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Multi-scale context aggregation by dilated convolutions,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Observation 9e60a88d-a5e2-432b-9b53-b0983d8ee5bf · outbound

This paper cites Squeeze-and-excitation networks,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Squeeze-and-excitation networks,

Reference 30

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Observation dac3a016-3b4a-4b1e-9d84-c29dcfdbdf9e · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning The surprising effectiveness of ppo in cooperative multi-agent games,

Reference 31

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Observation 11297e6b-88bb-4247-b5ae-bf2811310aec · outbound

This paper cites Multi-agent actor-critic for mixed cooperative-competitive environ- ments,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Multi-agent actor-critic for mixed cooperative-competitive environ- ments,

Reference 32

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Observation 0869f344-63e2-483c-8cc1-5c6df46a1cd9 · outbound

This paper cites Improving stochastic policy gradients in continuous control with deep reinforcement learning using the beta distribution,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Improving stochastic policy gradients in continuous control with deep reinforcement learning using the beta distribution,

Reference 33

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Observation b0abbc7f-c3b2-4969-bd54-ae198f8921ed · outbound

This paper cites Curriculum learning,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Curriculum learning,

Reference 34

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Observation 638838a7-8839-43d8-83d9-0191cdcb3e49 · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Domain randomization for transferring deep neural networks from simulation to the real world,

Reference 35

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Observation f322ee4e-3ccc-4eb8-8d55-185c048e3e38 · outbound

This paper cites Swarm-lio2: Decentralized, efficient lidar-inertial odometry for uav swarms,.

Decentralized End-to-End Multi-AAV Pursuit Using Predictive Spatio-Temporal Observation via Deep Reinforcement Learning Swarm-lio2: Decentralized, efficient lidar-inertial odometry for uav swarms,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-13T19:00:18.283733Z

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Pith citing papers

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