Paper Citation Record · LEDGER

Training Environment for High Performance Reinforcement Learning

As of 22 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2505.01953.

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

pith.paper-citation-record.v1
2505.01953 v1

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:09:21.778427Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

44 of 44 outbound references displayed

verified exact6
verified fuzzy28
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0f0038f1-102b-473c-a89e-5eed1b0fb06c · outbound

This paper cites TheNeedforCollaborative CombatAircraftforDisruptiveAirWarfare,.

Training Environment for High Performance Reinforcement Learning TheNeedforCollaborative CombatAircraftforDisruptiveAirWarfare,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.223299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f10128af-087d-4372-98ab-08794a1cf304 · outbound

This paper cites Air Force exercises two Collaborative Combat Aircraft option awards,.

Training Environment for High Performance Reinforcement Learning Air Force exercises two Collaborative Combat Aircraft option awards,

Reference 2

Resolution: verified exact; raw_fallback, observed 2026-08-16T04:09:22.487606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f562781e-a396-471e-8248-f43897c9013f · outbound

This paper cites Air Combat Evolution,.

Training Environment for High Performance Reinforcement Learning Air Combat Evolution,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.197979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9a504b23-1775-4616-bf5a-4939e726ce8f · outbound

This paper cites DARPA calling for AI ‘reinforcements’ to bolster US air combat capability,.

Training Environment for High Performance Reinforcement Learning DARPA calling for AI ‘reinforcements’ to bolster US air combat capability,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.164456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4ed5b6fa-6044-4e64-8b36-96490fd02c7e · outbound

This paper cites F-16s arrive to be modified for autonomous testing,.

Training Environment for High Performance Reinforcement Learning F-16s arrive to be modified for autonomous testing,

Reference 6

Resolution: verified exact; raw_fallback, observed 2026-08-16T04:09:22.376416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8034119e-30e8-4741-9e58-9a3eef5c9222 · outbound

This paper cites Airsim: High-fidelity visual and physical simulation for autonomous vehicles.

Training Environment for High Performance Reinforcement Learning Airsim: High-fidelity visual and physical simulation for autonomous vehicles

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.137579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 155c66cf-61eb-46ac-a72f-4809ef85b78a · outbound

This paper cites Learning to fly—a gym environment with pybullet physics for reinforcement learning of multiagent,.

Training Environment for High Performance Reinforcement Learning Learning to fly—a gym environment with pybullet physics for reinforcement learning of multiagent,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.112460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation efc5e096-2c00-4024-9e30-e8dad284be4b · outbound

This paper cites DCS World,.

Training Environment for High Performance Reinforcement Learning DCS World,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.087159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 54f76f36-b310-4b7e-a7c1-68647f0bcbee · outbound

This paper cites Flight Simulator X,.

Training Environment for High Performance Reinforcement Learning Flight Simulator X,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:23.065125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 87f57c17-64a0-4f78-8559-03394acad6dc · outbound

This paper cites an unresolved cited work.

Training Environment for High Performance Reinforcement Learning Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:09:23.033812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c83abcec-c933-468d-8fc0-e7be842b7578 · outbound

This paper cites Harfang3D Dog-Fight Sandbox: A Reinforcement Learning Research Platform for the Customized Control Tasks of Fighter Aircrafts.

Training Environment for High Performance Reinforcement Learning Harfang3D Dog-Fight Sandbox: A Reinforcement Learning Research Platform for the Customized Control Tasks of Fighter Aircrafts

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:09:22.287784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 336fcc71-0bfb-4853-8f1a-1f20769b6de2 · outbound

This paper cites Predictive Sampling: Real-time Behaviour Synthesis with MuJoCo.

Training Environment for High Performance Reinforcement Learning Predictive Sampling: Real-time Behaviour Synthesis with MuJoCo

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.555580Z

Source-reported events for the cited work

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Observation 5fa0aae1-8084-4440-aa52-716165dc267c · outbound

This paper cites The Arcade Learning Environment: An Evaluation Platform for General Agents.

Training Environment for High Performance Reinforcement Learning The Arcade Learning Environment: An Evaluation Platform for General Agents

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.562180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 191cbe3a-f65c-4ff7-a7a0-1b98c8bf84bf · outbound

This paper cites Quantifying Generalization in Reinforcement Learning.

Training Environment for High Performance Reinforcement Learning Quantifying Generalization in Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.569818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f75c843-b7f0-463f-9e7e-e5af3276b424 · outbound

This paper cites an unresolved cited work.

Training Environment for High Performance Reinforcement Learning Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:09:23.011082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ae142e93-82aa-43b9-bb5c-8c2e7a2df7cd · outbound

This paper cites Rule-based air combat simulation,.

Training Environment for High Performance Reinforcement Learning Rule-based air combat simulation,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.985056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a8d5bb67-2273-4a77-a3b3-f488fc0a8920 · outbound

This paper cites Air-combat strategy using approximate dynamic programming,.

Training Environment for High Performance Reinforcement Learning Air-combat strategy using approximate dynamic programming,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.960600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3fbde8d4-5340-4155-bed5-9952d29a4c19 · outbound

This paper cites SecAF Kendall experiences VISTA of future flight test at Edwards AFB,.

Training Environment for High Performance Reinforcement Learning SecAF Kendall experiences VISTA of future flight test at Edwards AFB,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.935617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9cff4a70-9741-491e-a3ec-7bc3cef2f1ec · outbound

This paper cites The New VISTA Simulation System Design and Implementation,.

Training Environment for High Performance Reinforcement Learning The New VISTA Simulation System Design and Implementation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.915125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 454dd41e-6c19-485b-b7a7-637d7ba3e26f · outbound

This paper cites Revealing the Dark Side of the F-16 - FLCS,.

Training Environment for High Performance Reinforcement Learning Revealing the Dark Side of the F-16 - FLCS,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.894573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 72878af8-c1e3-487e-92b8-c9dfadee80ce · outbound

This paper cites Fly by Wire Flight Control Systems,.

Training Environment for High Performance Reinforcement Learning Fly by Wire Flight Control Systems,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.873620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c4024589-1a83-4726-8e02-8809c2d287b3 · outbound

This paper cites Verification Challenges in F-16 Ground Collision Avoidance and Other Automated Maneuvers,.

Training Environment for High Performance Reinforcement Learning Verification Challenges in F-16 Ground Collision Avoidance and Other Automated Maneuvers,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.856904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 74f05d19-ac25-429e-a731-5d031307c313 · outbound

This paper cites an unresolved cited work.

Training Environment for High Performance Reinforcement Learning Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-16T04:09:22.837993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bb806378-9d60-45d6-82d7-ba0223e410ce · outbound

This paper cites W.,A Dictionary of Aviation, Osprey Publishing, 2016.

Training Environment for High Performance Reinforcement Learning W.,A Dictionary of Aviation, Osprey Publishing, 2016

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.813635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2418f057-e85d-45c4-9e6e-332844dde3be · outbound

This paper cites PID/First-Order Control Design for a Bank of F-16 Longitudinal Dynamic Systems,.

Training Environment for High Performance Reinforcement Learning PID/First-Order Control Design for a Bank of F-16 Longitudinal Dynamic Systems,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.787618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 163fd82e-28bf-42d7-ab7f-b90c167b77d2 · outbound

This paper cites USAF Finishes Flight Tests of F-16 Autonomous Gun System ,.

Training Environment for High Performance Reinforcement Learning USAF Finishes Flight Tests of F-16 Autonomous Gun System ,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.747770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c7f73beb-92e6-4a39-8df3-4c63b1abf37b · outbound

This paper cites A survey of air combat behavior modeling using machine learning ,.

Training Environment for High Performance Reinforcement Learning A survey of air combat behavior modeling using machine learning ,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.654890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 683030c3-1844-47df-9d1b-e2d7b398352d · outbound

This paper cites Imitation learning for modelling air combat behaviour,.

Training Environment for High Performance Reinforcement Learning Imitation learning for modelling air combat behaviour,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.726737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 38ecd24c-bc85-400f-ab0c-cfbc4c0a3ea9 · outbound

This paper cites Robust flight navigation out of distribution with liquid neural networks,.

Training Environment for High Performance Reinforcement Learning Robust flight navigation out of distribution with liquid neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.704842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cb5fd33f-6095-4410-afed-70e631459a7b · outbound

This paper cites Hierarchical Reinforcement Learning for Air Combat at DARPA's AlphaDogfight Trials.

Training Environment for High Performance Reinforcement Learning Hierarchical Reinforcement Learning for Air Combat at DARPA's AlphaDogfight Trials

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:09:22.101765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fb04894c-80eb-4bef-bc15-e1d5b3d4bd7b · outbound

This paper cites Viper Shield All Digital Electronic Warfare Suite,.

Training Environment for High Performance Reinforcement Learning Viper Shield All Digital Electronic Warfare Suite,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.685114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ace7fae5-9c13-4849-9386-9f9b02c4e6bf · outbound

This paper cites Resolving Range and Velocity Ambiguity Effectively and Efficiently with GPU,.

Training Environment for High Performance Reinforcement Learning Resolving Range and Velocity Ambiguity Effectively and Efficiently with GPU,

Reference 33

Resolution: verified exact; raw_fallback, observed 2026-08-16T04:09:22.069502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c5c04b3a-df9d-4c74-93e6-42aab4511f7d · outbound

This paper cites The Development and Use of an Inertial Navigation System as a DP Position Reference Sensor (IPRS),.

Training Environment for High Performance Reinforcement Learning The Development and Use of an Inertial Navigation System as a DP Position Reference Sensor (IPRS),

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.661773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3a23d594-48d1-4074-b38e-fc6cac2345ef · outbound

This paper cites Great Power Competition: Implications for Defense—Issues for Congress,.

Training Environment for High Performance Reinforcement Learning Great Power Competition: Implications for Defense—Issues for Congress,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.639874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e18bb222-a6a9-4daa-bad2-9690a043755e · outbound

This paper cites Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world.

Training Environment for High Performance Reinforcement Learning Nocturne: a scalable driving benchmark for bringing multi-agent learning one step closer to the real world

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.707697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 579e2a5d-2041-4513-952f-ff1f4535c8a0 · outbound

This paper cites Pentagon secures 500M for first tranche of Replicator systems,.

Training Environment for High Performance Reinforcement Learning Pentagon secures 500M for first tranche of Replicator systems,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.621112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 296949a0-1328-44f4-8607-a1284a559907 · outbound

This paper cites Viper Shield All Digital Electronic Warfare Suite,.

Training Environment for High Performance Reinforcement Learning Viper Shield All Digital Electronic Warfare Suite,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.601309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5352108d-9cbc-4b1a-8e8d-96f5bfdfd98f · outbound

This paper cites R.,Introduction to Aircraft Flight Mechanics: Performance, Static Stability, Dynamic Stability, Classic, AIAA Education Series, 2016.

Training Environment for High Performance Reinforcement Learning R.,Introduction to Aircraft Flight Mechanics: Performance, Static Stability, Dynamic Stability, Classic, AIAA Education Series, 2016

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.578633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 123fae42-8e7f-40ac-8405-8ce4207dca64 · outbound

This paper cites Automated Learning: An Implementation of The A* Search Algorithm over The Random Base Functions.

Training Environment for High Performance Reinforcement Learning Automated Learning: An Implementation of The A* Search Algorithm over The Random Base Functions

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-08-16T04:09:21.841904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de946f24-3be1-43e6-8a0f-7b0876a14ae2 · outbound

This paper cites Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning,.

Training Environment for High Performance Reinforcement Learning Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.558907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5d449e15-4ce1-4df9-bf48-e34e0751ccf5 · outbound

This paper cites LOYAL WINGMAN, FLOCKING, AND SWARMING: NEW MODELS OF DIS- TRIBUTED AIRPOWER,.

Training Environment for High Performance Reinforcement Learning LOYAL WINGMAN, FLOCKING, AND SWARMING: NEW MODELS OF DIS- TRIBUTED AIRPOWER,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.533955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 977411ec-c9b8-4e56-aad1-67e925954585 · outbound

This paper cites DARPA Tiles Together a Vision of Mosaic Warfare,.

Training Environment for High Performance Reinforcement Learning DARPA Tiles Together a Vision of Mosaic Warfare,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:09:22.508260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3bb2e378-e311-4c9b-b834-5c05a4ece309 · outbound

This paper cites Liquid Time-constant Networks.

Training Environment for High Performance Reinforcement Learning Liquid Time-constant Networks

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.483490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88c56777-fadb-46bb-a61a-cbd67d8fa189 · outbound

This paper cites Deployable Reinforcement Learning with Variable Control Rate.

Training Environment for High Performance Reinforcement Learning Deployable Reinforcement Learning with Variable Control Rate

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-16T04:09:21.748731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.