Paper Citation Record · LEDGER

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications

As of 15 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2502.12024.

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

pith.paper-citation-record.v1
2502.12024 v2

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:02:10.757657Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T20:32:54.607173Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T20:36:50.334353Z

Reference resolution

18 of 18 outbound references displayed

verified exact0
verified fuzzy12
unresolved2
parse uncertain0
malformed identifier3
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5ad239d8-2a47-4c9d-a4f9-b65036e47b8b · outbound

This paper cites Social Learning under Platform Influence: Consensus and Persistent Disagreement.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Social Learning under Platform Influence: Consensus and Persistent Disagreement

Reference 1

Resolution: metadata mismatch; local_arxiv, observed 2026-08-09T18:02:10.820026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9efa59cf-8846-4913-b710-15eb4169d0da · outbound

This paper cites The projected policy gradient update rule which is expressed as: σh+1 =P P(S×A) (σh +γ h∇σV(σ h)) (7) whereγ h denotes the learning rate at iterationh.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications The projected policy gradient update rule which is expressed as: σh+1 =P P(S×A) (σh +γ h∇σV(σ h)) (7) whereγ h denotes the learning rate at iterationh

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.998927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6e61bc08-8f39-415f-80db-667ee7792907 · outbound

This paper cites Specifically, we assume thatM:P(X)→ M ⊂R n, whereMis a compact set.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Specifically, we assume thatM:P(X)→ M ⊂R n, whereMis a compact set

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.965994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 64e901fd-c6e0-4e73-933e-ce090097ccfc · outbound

This paper cites Fatou’s lemma for weakly converging measures under the uniform integrability condition,.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Fatou’s lemma for weakly converging measures under the uniform integrability condition,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:11.076881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fb64b93e-0089-4ea3-af23-b84fe42ee1d6 · outbound

This paper cites , H, yielding policy ˆgt(x, mt).

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications , H, yielding policy ˆgt(x, mt)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.982107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c5995228-3f0e-4dcf-80d0-257cab68247b · outbound

This paper cites The scalar interaction function is the mean field limit of this finite retailers case.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications The scalar interaction function is the mean field limit of this finite retailers case

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.948065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1181dc12-3a48-4f50-907c-c5c7eb8efa87 · outbound

This paper cites A similar regenerative framework for arrivals and departures is discussed in other MFE models (e.g., Iyer et al.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications A similar regenerative framework for arrivals and departures is discussed in other MFE models (e.g., Iyer et al

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.932782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7a177bcd-c3f0-4d6c-817d-3d51ae22b3dd · outbound

This paper cites an unresolved cited work.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Unresolved cited work

Reference 13

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T18:02:10.918121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation daf0e88d-92a9-42ab-8449-ff786d0bd999 · outbound

This paper cites Proof of Theorem 2.Lettbe some iteration of the algorithm.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Proof of Theorem 2.Lettbe some iteration of the algorithm

Reference 14

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T18:02:10.902300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a72c0d99-8450-4929-8b36-184610ebfa3e · outbound

This paper cites Hence, ∆V (0, a) = (1−δ)h′ 1(a)V(1, m) + (−h′ 1(a) +δh ′ 1(a))V(0, m) =h′ 1(a)(1−δ)∆V(0, m).

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Hence, ∆V (0, a) = (1−δ)h′ 1(a)V(1, m) + (−h′ 1(a) +δh ′ 1(a))V(0, m) =h′ 1(a)(1−δ)∆V(0, m)

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.885155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7a5dae62-f853-49ae-b01e-c880edf5ecd6 · outbound

This paper cites Part (ii) shows thatgis increasing inx.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Part (ii) shows thatgis increasing inx

Reference 16

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T18:02:10.869577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7eb58694-7e0f-41db-9cd4-632f149a4341 · outbound

This paper cites This is typically satisfied in many practical settings, including cases whereM(s) represents the expected value operator.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications This is typically satisfied in many practical settings, including cases whereM(s) represents the expected value operator

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:10.853164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3d667cd5-b756-4378-8288-28caf067737d · outbound

This paper cites an unresolved cited work.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-09T18:02:10.836828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1adbdcca-e93f-4406-803d-1bad3e53007e · outbound

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

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Learning in Mean Field Games: A Survey

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T18:02:10.698396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 827568a2-fa13-4310-a5e4-a308a611d147 · outbound

This paper cites A general framework for learning mean-field games,.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications A general framework for learning mean-field games,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:11.046730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f9645c4c-5d96-4ca9-9850-ae63ca8a11ca · outbound

This paper cites Learning while playing in mean-field games: Convergence and optimality,.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Learning while playing in mean-field games: Convergence and optimality,

Reference 1265

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:11.016491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 762b2620-a6d1-4ef2-88c6-8a12c87dc46f · outbound

This paper cites Your uber is arriving: Managing on-demand workers through surge pricing, forecast communication, and worker incentives,.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Your uber is arriving: Managing on-demand workers through surge pricing, forecast communication, and worker incentives,

Reference 3235

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:11.062154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8cd5c702-f470-4c3f-abbe-fcc955169ba9 · outbound

This paper cites Markov perfect industry dynamics with many firms,.

Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications Markov perfect industry dynamics with many firms,

Reference 6715

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:02:11.031744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation 958600f5-5495-4825-99af-35c385e310be · inbound

Approximation of Discrete-Time Infinite-Horizon Mean-Field Equilibria via Finite-Horizon Mean-Field Equilibria cites this paper.

Approximation of Discrete-Time Infinite-Horizon Mean-Field Equilibria via Finite-Horizon Mean-Field Equilibria Computing and Learning Stationary Mean Field Equilibria with Scalar Interactions: Algorithms and Applications

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:36:50.336970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.