Paper Citation Record · LEDGER

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games

As of 15 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2502.00915.

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

pith.paper-citation-record.v1
2502.00915 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T17:29:42.757038Z

measured 16 of 16 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

16 of 16 outbound references displayed

verified exact1
verified fuzzy9
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 001b97d0-46fd-48d7-ae24-0f502726238d · outbound

This paper cites Hysteretic q-learning: an algorithm for decentralized reinforcement learning in cooperative multi-agent teams.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Hysteretic q-learning: an algorithm for decentralized reinforcement learning in cooperative multi-agent teams

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.244840Z

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 4a08e0f7-a8ce-4d9c-b0b8-bdb17ac2902a · outbound

This paper cites Independent Learning in Stochastic Games.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Independent Learning in Stochastic Games

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T17:29:42.625786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90c4c537-71bf-415c-9499-0c29b89d67ed · outbound

This paper cites Tor Metrics.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Tor Metrics

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.214727Z

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 d06ca2f9-99c7-4ac1-aadc-5131e9c22380 · outbound

This paper cites Theboundinthestatementofthetheoreminthemainbodyofthepaperfollowsfromthe fact that the lengths of the exploration epochs scale withTh = O(ε−1 log(h + 2)) = eO(ε−1).

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Theboundinthestatementofthetheoreminthemainbodyofthepaperfollowsfromthe fact that the lengths of the exploration epochs scale withTh = O(ε−1 log(h + 2)) = eO(ε−1)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.032934Z

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 4070aa1e-d17d-44ef-9945-112b0bb37e97 · outbound

This paper cites Mean-Field Games With Finitely Many Players: Independent Learning and Subjectivity.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Mean-Field Games With Finitely Many Players: Independent Learning and Subjectivity

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-09T17:29:42.826157Z

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 f3751ff8-6ce6-4be6-9c54-c3fa333f248f · outbound

This paper cites Learning regularized monotonegraphonmean-fieldgames.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Learning regularized monotonegraphonmean-fieldgames

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.180495Z

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 ffdc0b02-8422-4053-a7c8-c481e4f1abea · outbound

This paper cites In the work of Gummadi et al.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games In the work of Gummadi et al

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.148751Z

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 e4ee7fcd-446f-43b3-8391-c2df482bf734 · outbound

This paper cites However, in Figure 7 we provide comparison with a heuristic extension of the OMD algorithm proposed by Pérolat et al.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games However, in Figure 7 we provide comparison with a heuristic extension of the OMD algorithm proposed by Pérolat et al

Reference 1000

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:42.972084Z

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 c3da5db0-4355-46be-abac-fca2815b4609 · outbound

This paper cites Simple and optimal methods for stochas- tic variational inequalities, i: Operator extrapolation.SIAM Journal on Optimization, 32 (3):2041–2073,.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Simple and optimal methods for stochas- tic variational inequalities, i: Operator extrapolation.SIAM Journal on Optimization, 32 (3):2041–2073,

Reference 1976

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.259324Z

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 fb476bb6-4800-4f6b-9aab-99adbcf43be7 · outbound

This paper cites Shining light in dark places: Understanding the tor network.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Shining light in dark places: Understanding the tor network

Reference 2007

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.230256Z

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 80bd2b82-aee0-4d17-a2fa-74d0e8f5fc7b · outbound

This paper cites an unresolved cited work.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Unresolved cited work

Reference 2013

Resolution: unresolved; raw_fallback, observed 2026-08-09T17:29:43.165257Z

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 99b9113b-36e6-4d75-a078-a93ac96d5272 · outbound

This paper cites Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T17:29:42.699801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f82252d-cc4f-4fde-8f0b-458d0bec97b8 · outbound

This paper cites Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-09T17:29:42.716190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc4e08c-2423-4d20-b9ae-f4ea91ca289e · outbound

This paper cites Concurrent bandits and cognitive radio networks.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Concurrent bandits and cognitive radio networks

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T17:29:43.274408Z

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 803af656-747a-40ce-9071-6dcfb43977c9 · outbound

This paper cites an unresolved cited work.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-09T17:29:43.197213Z

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 39aa5e96-9a13-40f7-88f7-82e3f2a639cc · outbound

This paper cites Learning in Mean Field Games: A Survey.

A Variational Inequality Approach to Independent Learning in Static Mean-Field Games Learning in Mean Field Games: A Survey

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-09T17:29:42.466016Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.