Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1901.09311.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T16:18:17.386389Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T16:15:16.199680Z
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 e73cbf13-dca9-4c8c-b6d9-743b092cd34e · inbound
Concurrent Learning with Aggregated States via Randomized Least Squares Value Iteration cites this paper.
Concurrent Learning with Aggregated States via Randomized Least Squares Value Iteration Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T16:18:17.386389Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adca8aff-9532-4ec8-85aa-12f2d1a0e8a3 · inbound
Statistical and Algorithmic Foundations of Reinforcement Learning cites this paper.
Statistical and Algorithmic Foundations of Reinforcement Learning Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
Reference 34
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T16:15:16.203077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4c7bf4ac-ee8b-40aa-8ac7-de0c812c5dc2 · inbound
Asymptotically Optimal Regret for Reinforcement Learning without Horizon Dependence cites this paper.
Asymptotically Optimal Regret for Reinforcement Learning without Horizon Dependence Q-learning with UCB Exploration is Sample Efficient for Infinite-Horizon MDP
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T11:40:23.836348Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.