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Paper Citation Record · LEDGER

Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1602.02672.

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

pith.paper-citation-record.v1
1602.02672 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:04:02.046701Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T13:47:05.746965Z

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 5e4718cb-7f45-4e1f-8103-1c7b30f56219 · inbound

Dynamic Graph Communication for Decentralised Multi-Agent Reinforcement Learning cites this paper.

Dynamic Graph Communication for Decentralised Multi-Agent Reinforcement Learning Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-10T23:04:02.046701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:04:02.046701Z digest=sha256:9f80568d5adc3d17c4b05168524861cf127e2b742d5b0b8c62896e74ce2727cc

Observation f59dad1a-5d5f-4c46-8841-5616f2322f74 · inbound

Generative Emergent Communication: Large Language Model is a Collective World Model cites this paper.

Generative Emergent Communication: Large Language Model is a Collective World Model Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-10T23:01:42.796855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:01:42.796855Z digest=sha256:3d32f6225f1a5af8b5499aeb0c72b38155386b88aed7f04b1de7ccbaaf3db2cf

Observation 5bf1adff-5cc1-4763-9807-51157cea4c68 · inbound

Provably Optimal Learning Algorithms for Assistance Games cites this paper.

Provably Optimal Learning Algorithms for Assistance Games Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-07-10T13:47:05.748441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-07-10T13:46:04.338440Z digest=sha256:749b8d7cceeae3543df02c3a7d3ba8ef64c876ccc33d860fab975c9e37329b46