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Paper Citation Record · LEDGER

Opponent Modeling in Deep Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:1609.05559.

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

pith.paper-citation-record.v1
1609.05559 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 1 of 1 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T20:27:51.640523Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 d63c9389-ba11-43ea-86c5-485341934d00 · inbound

AI-Augmented Model Predictive Control for Safe and Adaptive Rendezvous and Proximity Operations cites this paper.

AI-Augmented Model Predictive Control for Safe and Adaptive Rendezvous and Proximity Operations Opponent Modeling in Deep Reinforcement Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-01T20:27:51.640523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T20:27:51.640523Z digest=sha256:efb1fdaf0eaa2a26b135c0f2f66c88a3f86e76a4af48fe9a9a941f1b147a2bf2