Paper Citation Record · LEDGER

Discounted Reinforcement Learning Is Not an Optimization Problem

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1910.02140.

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

pith.paper-citation-record.v1
1910.02140 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:18:54.476829Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T17:35:00.853668Z

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 1b6fd44b-c44c-4368-894a-37436948a5c3 · inbound

Average-Reward Soft Actor-Critic cites this paper.

Average-Reward Soft Actor-Critic Discounted Reinforcement Learning Is Not an Optimization Problem

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:13:57.580973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22b76259-2cec-4a0e-bbd6-fe5c3402b724 · inbound

EVAL: EigenVector-based Average-reward Learning cites this paper.

EVAL: EigenVector-based Average-reward Learning Discounted Reinforcement Learning Is Not an Optimization Problem

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T20:18:54.476829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef9f9df8-47c7-4518-9ebb-4a997b1ebe92 · inbound

From Set Convergence to Pointwise Convergence: Finite-Time Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes cites this paper.

From Set Convergence to Pointwise Convergence: Finite-Time Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes Discounted Reinforcement Learning Is Not an Optimization Problem

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-22T17:35:00.856976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 9953429e-a13c-4914-903b-1ae69b8e7029 · inbound

Isomorphic Dynamic Programs cites this paper.

Isomorphic Dynamic Programs Discounted Reinforcement Learning Is Not an Optimization Problem

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T02:50:58.395784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.