Paper Citation Record · LEDGER

Light Aircraft Game : Basic Implementation and training results analysis

As of 20 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2506.14164.

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

pith.paper-citation-record.v1
2506.14164 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:23:07.922367Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

9 of 9 outbound references displayed

verified exact0
verified fuzzy0
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1cff9fb9-eb41-4802-a372-4046bfc8210e · outbound

This paper cites Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning.

Light Aircraft Game : Basic Implementation and training results analysis Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.654898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40197884-7218-4cbc-9eda-ab5aeab03682 · outbound

This paper cites The StarCraft Multi-Agent Challenge.

Light Aircraft Game : Basic Implementation and training results analysis The StarCraft Multi-Agent Challenge

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.922367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcb8afab-e417-4282-b540-c6b2ce505fd0 · outbound

This paper cites A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem.

Light Aircraft Game : Basic Implementation and training results analysis A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.583998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bbe5760f-2516-4c4f-89ca-0910f1e1fae7 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Light Aircraft Game : Basic Implementation and training results analysis Soft Actor-Critic Algorithms and Applications

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.506079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c7a71b39-099c-497a-b166-ee3f0ee49430 · outbound

This paper cites Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?.

Light Aircraft Game : Basic Implementation and training results analysis Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.338517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba6cdf49-57b7-4178-9cc2-847b9bc158a0 · outbound

This paper cites FACMAC: Factored Multi-Agent Centralised Policy Gradients.

Light Aircraft Game : Basic Implementation and training results analysis FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.846834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e50c70c0-41c5-4384-993f-6d874788ef74 · outbound

This paper cites Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning.

Light Aircraft Game : Basic Implementation and training results analysis Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.321075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 394f1c3e-d73e-48ac-9497-39555c94c967 · outbound

This paper cites SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning.

Light Aircraft Game : Basic Implementation and training results analysis SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.425085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85117d10-7982-41e9-95d2-7b098201d34d · outbound

This paper cites Maximum Entropy Heterogeneous-Agent Reinforcement Learning.

Light Aircraft Game : Basic Implementation and training results analysis Maximum Entropy Heterogeneous-Agent Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T00:23:07.736906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.