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Paper Citation Record · LEDGER

Mean Field Multi-Agent Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1802.05438.

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

pith.paper-citation-record.v1
1802.05438 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:58:36.323593Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T17:58:36.914001Z

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 aea3fa6f-1a0b-4e5e-86f0-0cc60e3d9a8c · inbound

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning cites this paper.

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning Mean Field Multi-Agent Reinforcement Learning

Reference 2018

Resolution
metadata mismatch
local_arxiv, observed 2026-08-09T17:58:36.919736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-09T17:58:36.323593Z digest=sha256:f1da334337fdb760ce211c1e72408ee4b01e3820cbf9e38735926155044b1ea7

Observation 06a153f4-1aa4-46a5-b06f-2d147f90b1cb · inbound

The Theory of Strategic Evolution: Games with Endogenous Players and Strategic Replicators cites this paper.

The Theory of Strategic Evolution: Games with Endogenous Players and Strategic Replicators Mean Field Multi-Agent Reinforcement Learning

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-03T18:18:52.227182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T18:18:52.227182Z digest=sha256:6c8b96ba3f087eafa96da24e4676ef813f8383aa41df8855a998be394d5824f3