Paper Citation Record · LEDGER

Asymptotically optimal regret in communicating Markov decision processes

As of 15 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2505.18064.

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

pith.paper-citation-record.v1
2505.18064 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:41:53.055380Z

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

11 of 11 outbound references displayed

verified exact2
verified fuzzy2
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b97480b8-281b-492d-a57e-531ff7779aa3 · outbound

This paper cites The regret lower bound for communicating Markov Decision Processes.

Asymptotically optimal regret in communicating Markov decision processes The regret lower bound for communicating Markov Decision Processes

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:52.317140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1177cdb-2798-4a64-9447-616a5d833687 · outbound

This paper cites Thompson Sampling: An Asymptotically Optimal Finite Time Analysis.

Asymptotically optimal regret in communicating Markov decision processes Thompson Sampling: An Asymptotically Optimal Finite Time Analysis

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:52.699755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59780be3-1494-4337-9bc4-08bd81a43143 · outbound

This paper cites Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities.

Asymptotically optimal regret in communicating Markov decision processes Near-optimal Optimistic Reinforcement Learning using Empirical Bernstein Inequalities

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:52.867553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8f64276-0b8f-4855-882f-859cd0eab264 · outbound

This paper cites 2 2.1.1 Randomized policies, their gain, bias & gap functions.

Asymptotically optimal regret in communicating Markov decision processes 2 2.1.1 Randomized policies, their gain, bias & gap functions

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:54.230041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4f545917-448a-4995-90a0-eae6717909f2 · outbound

This paper cites Shipra Agrawal and Navin Goyal.

Asymptotically optimal regret in communicating Markov decision processes Shipra Agrawal and Navin Goyal

Reference 1988

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T14:41:54.076804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e787acf3-7951-4e31-b64d-2be6d3e1ae14 · outbound

This paper cites OptimisminReinforcementLearningand Kullback-Leibler Divergence.2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 115–122, September.

Asymptotically optimal regret in communicating Markov decision processes OptimisminReinforcementLearningand Kullback-Leibler Divergence.2010 48th Annual Allerton Conference on Communication, Control, and Computing (Allerton), pages 115–122, September

Reference 2006

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:41:54.432856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation aa5e2e6b-1d62-480e-ada3-dfe14b0cbdb4 · outbound

This paper cites Optimism in Reinforcement Learning and Kullback-Leibler Divergence.

Asymptotically optimal regret in communicating Markov decision processes Optimism in Reinforcement Learning and Kullback-Leibler Divergence

Reference 2010

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:41:53.465716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4dcb854f-c078-4950-baf7-133786970846 · outbound

This paper cites Analysis of Thompson Sampling for the multi-armed bandit problem.

Asymptotically optimal regret in communicating Markov decision processes Analysis of Thompson Sampling for the multi-armed bandit problem

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:52.078339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f77ad02a-93d7-4232-9cd3-b69d95b5a342 · outbound

This paper cites Improved Analysis of UCRL2 with Empirical Bernstein Inequality.

Asymptotically optimal regret in communicating Markov decision processes Improved Analysis of UCRL2 with Empirical Bernstein Inequality

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T14:41:52.529881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25ad5aad-bcea-4ec1-a0a9-b4747667d607 · outbound

This paper cites Regret Analysis in Deterministic Reinforcement Learning.

Asymptotically optimal regret in communicating Markov decision processes Regret Analysis in Deterministic Reinforcement Learning

Reference 2021

Resolution: metadata mismatch; local_arxiv, observed 2026-08-07T14:41:53.279499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7f096932-4b03-4d01-afc6-f1398f33e713 · outbound

This paper cites _eprint: 2502.06480.

Asymptotically optimal regret in communicating Markov decision processes _eprint: 2502.06480

Reference 2025

Resolution: verified exact; raw_fallback, observed 2026-08-07T14:41:53.838157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

No inbound Pith citation observations are available.