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Paper Citation Record · LEDGER

Empirically Evaluating Multiagent Learning Algorithms

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1401.8074.

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

pith.paper-citation-record.v1
1401.8074 v1

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 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:59:09.687442Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T10:45:48.455092Z

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 2b540260-e78e-4fbe-b36b-3819a30e8c74 · inbound

A Review of Cooperative Multi-Agent Deep Reinforcement Learning cites this paper.

A Review of Cooperative Multi-Agent Deep Reinforcement Learning Empirically Evaluating Multiagent Learning Algorithms

Reference 214

Resolution
unresolved
no resolver link, observed 2026-08-14T13:59:09.687442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:59:09.687442Z digest=sha256:d3098772ea3588639ee6ee6be6e1f83eb63be25536e4797e2866a68bc3f3c33d

Observation 66cab8c5-69ca-4792-9acd-4c172d509005 · inbound

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control cites this paper.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Empirically Evaluating Multiagent Learning Algorithms

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:45:48.464842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-14T10:45:48.188074Z digest=sha256:1f2cc7e1fe99ed05ad5810e76c0a9a5ff509ae49b71ac74c97e84db5fee72075