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Paper Citation Record · LEDGER

A Review of Cooperative Multi-Agent Deep Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1908.03963.

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

pith.paper-citation-record.v1
1908.03963 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:35:05.226971Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T00:04:06.029962Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9df3cee5-0af7-4578-ae75-5a6e7c5259b1 · inbound

CH-MARL: Constrained Hierarchical Multiagent Reinforcement Learning for Sustainable Maritime Logistics cites this paper.

CH-MARL: Constrained Hierarchical Multiagent Reinforcement Learning for Sustainable Maritime Logistics A Review of Cooperative Multi-Agent Deep Reinforcement Learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T13:35:05.226971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T13:35:05.226971Z digest=sha256:893eae20b9d063d7bef35feebd510085dc47722c6403321e5f830d59b902fe60

Observation b00483d2-0ae5-47be-bb98-3c184e961403 · inbound

MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning cites this paper.

MEAL: A Benchmark for Continual Multi-Agent Reinforcement Learning A Review of Cooperative Multi-Agent Deep Reinforcement Learning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T00:16:44.730375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:16:44.730375Z digest=sha256:2497151f4e2118bcf2bf1dbdcddd70a2c7f101bd9927dbfd1ebf609e29900483

Observation c3c3d3c4-d561-43ac-83cb-8d25a320de4a · inbound

Quantum Advantage in Multi Agent Reinforcement Learning cites this paper.

Quantum Advantage in Multi Agent Reinforcement Learning A Review of Cooperative Multi-Agent Deep Reinforcement Learning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-15T01:48:28.091442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T01:47:50.831972Z digest=sha256:78ffaec18ae0b0860d46a1f49cf918864d94ba469c0e248b1346d02f5c59e588

Observation 30c09900-b80a-444f-be8d-89cd4f303b65 · inbound

Scaling up Energy-Aware Multi-Agent Reinforcement Learning for Mission-Oriented Drone Networks with Individual Reward cites this paper.

Scaling up Energy-Aware Multi-Agent Reinforcement Learning for Mission-Oriented Drone Networks with Individual Reward A Review of Cooperative Multi-Agent Deep Reinforcement Learning

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-06-30T00:04:06.031488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T23:59:46.054657Z digest=sha256:84f1f3bded6843d82dea52c837c54c3cf27df839dc4e2b8aa0253b53026ca4e8

Observation a8e1ce44-a2bb-4163-a30f-f271ce7f8355 · inbound

Integrated Altruistic and Fairness Preference Induces Advanced Mutual Cooperation in Sequential Social Dilemmas cites this paper.

Integrated Altruistic and Fairness Preference Induces Advanced Mutual Cooperation in Sequential Social Dilemmas A Review of Cooperative Multi-Agent Deep Reinforcement Learning

Reference 27

Resolution
unresolved
no resolver link, observed 2026-07-11T14:47:06.125148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T14:47:06.125148Z digest=sha256:1eee128d01ace4c0c6e3c2bddf73178d91e2c0c97b9434a691b5e34db3e6821c