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Paper Citation Record · LEDGER

A Survey on Physics Informed Reinforcement Learning: Review and Open Problems

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2309.01909.

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

pith.paper-citation-record.v1
2309.01909 v1

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 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:48:31.169274Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T19:18:54.913266Z

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 ab84391e-53dc-4b56-892f-deb3d83572fa · inbound

Coordinated Power Smoothing Control for Wind Storage Integrated System with Physics-informed Deep Reinforcement Learning cites this paper.

Coordinated Power Smoothing Control for Wind Storage Integrated System with Physics-informed Deep Reinforcement Learning A Survey on Physics Informed Reinforcement Learning: Review and Open Problems

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T13:48:31.169274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:48:31.169274Z digest=sha256:3aa18943c08ee39b2e148d17c3282174a5b089daa44e7ec19e8a18167e3a7b1f

Observation 9c7f80c5-7dd9-49d8-b555-71f9eebd0cf5 · inbound

SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning cites this paper.

SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning A Survey on Physics Informed Reinforcement Learning: Review and Open Problems

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:42:26.293441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-23T02:40:03.682435Z digest=sha256:9985cc9a1949f1f16b29a8ea1bf292405ed2697aad2ab90c5d5b6d5df73889cc

Observation e5951502-53c2-40d6-b215-785bc9097516 · inbound

Self-Evolving Scientific Agent Discovers Generalizable Physically-Reasoned Fluid Control cites this paper.

Self-Evolving Scientific Agent Discovers Generalizable Physically-Reasoned Fluid Control A Survey on Physics Informed Reinforcement Learning: Review and Open Problems

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:17:25.911423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T19:05:54.202107Z digest=sha256:67a9ae33121a8711b6940e6db066498e4520e5db911dca2cedaafeff8261fc2e

Observation 4c5a4853-fe25-40a0-a108-04d13c686595 · inbound

TRIDENT: Breaking the Hybrid-Safety-Physics Coupling for Provably Safe Multi-Agent Reinforcement Learning cites this paper.

TRIDENT: Breaking the Hybrid-Safety-Physics Coupling for Provably Safe Multi-Agent Reinforcement Learning A Survey on Physics Informed Reinforcement Learning: Review and Open Problems

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-03T19:18:54.915650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-27T01:54:19.216553Z digest=sha256:f5cc38b432be6f6905a5c72df7a18b7d24171bd51895530eb54675a69f2b2472

Observation 0c09a105-60a2-4545-8132-686ad2897dcc · inbound

Physics-enhanced reinforcement learning for real-time optimal control of dynamical systems cites this paper.

Physics-enhanced reinforcement learning for real-time optimal control of dynamical systems A Survey on Physics Informed Reinforcement Learning: Review and Open Problems

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-01T21:11:44.232207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T21:11:44.232207Z digest=sha256:bafb4d3b3aa74e18f2cfbdaa7692b5243f9faebcecfee960db0f3718f01f1a95