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Integrity report for Chebyshev Policies and the Mountain Car Problem: Reinforcement Learning for Low-Dimensional Control Tasks

A machine-verified record of the checks Pith has run against this paper: detector runs, findings, signed bundle events, and canonical identifiers.

arXiv:2605.22305 · pith:2026:2WF4A5LGH46JXO34TQUZYYCOXM

0Critical
0Advisory
7Detectors run
2026-05-28Last checked

Paper page arXiv integrity.json bundle.json

Detector runs

doi_compliance completed v1.0.0 · findings 0 · 2026-05-28 08:15:07.738703+00:00
doi_title_agreement completed v1.0.0 · findings 0 · 2026-05-28 08:03:30.478255+00:00
claim_evidence completed v1.0.0 · findings 0 · 2026-05-27 12:24:27.477493+00:00
citation_quote_validity completed v0.1.0 · findings 0 · 2026-05-24 17:50:59.851007+00:00
shingle_duplication completed v0.1.0 · findings 0 · 2026-05-23 17:50:12.329662+00:00
cited_work_retraction completed v1.0.0 · findings 0 · 2026-05-22 09:52:40.255680+00:00
ai_meta_artifact skipped v1.0.0 · findings 0 · 2026-05-22 01:33:42.759270+00:00

Findings

No public integrity findings for this paper.

Signed record

The machine-readable record for this paper lives at /pith/2WF4A5LG/integrity.json. Pith Number bundles also include signed pith.integrity.v1 events where a Pith Number exists.