Paper Citation Record · LEDGER

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2509.03030.

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

pith.paper-citation-record.v1
2509.03030 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:38:32.978586Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ec1ba86-a4af-453a-9b15-f214bdfe06fb · outbound

This paper cites Multi-agent systems: A survey,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Multi-agent systems: A survey,

Reference 1

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Observation 987f944a-6e6f-42b5-9754-72f97f215eab · outbound

This paper cites Flocking for multi-agent dynamic systems: Algorithms and theory,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Flocking for multi-agent dynamic systems: Algorithms and theory,

Reference 2

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Observation 233fee0a-9807-4f42-8edc-44b7f5d3a242 · outbound

This paper cites Emergent behavior in flocks,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Emergent behavior in flocks,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:35.242337Z

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Observation 201cb459-857d-4629-a17e-8f89d242d9d9 · outbound

This paper cites Application of multi- agent systems in traffic and transportation,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Application of multi- agent systems in traffic and transportation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:35.119595Z

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Observation e2cf963e-2a89-4fac-b151-0c44a3bbd298 · outbound

This paper cites A survey on aerial swarm robotics,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning A survey on aerial swarm robotics,

Reference 5

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Observation 7f01d84d-06d6-42c9-87cf-e4a8a55aaeff · outbound

This paper cites Multi-agent actor-critic for mixed cooperative-competitive environments,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Multi-agent actor-critic for mixed cooperative-competitive environments,

Reference 6

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Observation 435b6328-e272-48ba-8c0a-eb172e5bdd3d · outbound

This paper cites Monotonic value function factorisation for deep multi-agent reinforcement learning,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Monotonic value function factorisation for deep multi-agent reinforcement learning,

Reference 7

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Observation 1f7f8a3d-14ab-4631-a123-b7fd7f0cf084 · outbound

This paper cites Mean field games,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Mean field games,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.996585Z

Source-reported events for the cited work

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Observation c11c0ba5-90de-46c7-a7c2-5ad5e42e0fc3 · outbound

This paper cites Large-population cost- coupled lqg problems with nonuniform agents: individual-mass behavior and decentralized ε-nash equilibria,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Large-population cost- coupled lqg problems with nonuniform agents: individual-mass behavior and decentralized ε-nash equilibria,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.827610Z

Source-reported events for the cited work

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Observation 3a95b0ab-6eb1-4deb-b741-268013389a21 · outbound

This paper cites Carmona and F.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Carmona and F

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.771857Z

Source-reported events for the cited work

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Observation 4dfbe4e6-cc04-462c-9779-4908e7ab291f · outbound

This paper cites Bensoussan, J.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Bensoussan, J

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.748046Z

Source-reported events for the cited work

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Observation 310eaab3-d30c-407e-8ea9-86e368b581f3 · outbound

This paper cites Efficient ridesharing order dispatching with mean field multi-agent reinforcement learning,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Efficient ridesharing order dispatching with mean field multi-agent reinforcement learning,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.724328Z

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Observation 9f9102a1-6dec-4340-8951-e489c2bc7bd6 · outbound

This paper cites Learning mean-field games,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Learning mean-field games,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.523785Z

Source-reported events for the cited work

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Observation d400de0e-eee9-46fe-b81a-2bbc2f7cfe63 · outbound

This paper cites Approximately solving mean field games via entropy-regularized deep reinforcement learning,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Approximately solving mean field games via entropy-regularized deep reinforcement learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.362940Z

Source-reported events for the cited work

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Observation e9e27898-0cf2-4f0d-8452-2c8a775d3c72 · outbound

This paper cites Q-learning in regularized mean-field games,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Q-learning in regularized mean-field games,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.342630Z

Source-reported events for the cited work

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Observation 00ad712a-4880-4d58-8011-52b86aa777f3 · outbound

This paper cites Iterative solution of games by fictitious play,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Iterative solution of games by fictitious play,

Reference 16

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Observation 529ac6f3-403b-4a88-8cf3-e016c3735c71 · outbound

This paper cites Brown’s original fictitious play,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Brown’s original fictitious play,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.292562Z

Source-reported events for the cited work

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Observation 3c334c90-7280-4629-9e0b-2e0f908a661d · outbound

This paper cites Learning in mean field games: the fictitious play,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Learning in mean field games: the fictitious play,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:34.263429Z

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Observation 622090f4-49c9-456b-82d8-033d6cb142ae · outbound

This paper cites Finite mean field games: fictitious play and convergence to a first order continuous mean field game,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Finite mean field games: fictitious play and convergence to a first order continuous mean field game,

Reference 19

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Observation e278b5f9-d856-46b0-993e-39eecd09f08e · outbound

This paper cites Fictitious play for mean field games: Continuous time analysis and applications,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Fictitious play for mean field games: Continuous time analysis and applications,

Reference 20

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Observation 598eb8ae-f40c-4c95-a373-923bc753bdb0 · outbound

This paper cites Scalable deep rein- forcement learning algorithms for mean field games,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Scalable deep rein- forcement learning algorithms for mean field games,

Reference 21

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Observation 78691f11-f9f9-4b3d-8986-1af9b608b9a0 · outbound

This paper cites Learning in anonymous nonatomic games with applications to first-order mean field games.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Learning in anonymous nonatomic games with applications to first-order mean field games

Reference 22

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Observation 9f29739b-88eb-4af8-9a1d-29de427dc6ca · outbound

This paper cites Hadikhanloo, Learning in mean field games.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Hadikhanloo, Learning in mean field games

Reference 23

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Observation e4148aeb-8995-4d98-92cc-d359609e938e · outbound

This paper cites Scaling mean field games by online mirror descent,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Scaling mean field games by online mirror descent,

Reference 24

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This paper cites Munchausen reinforcement learning,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Munchausen reinforcement learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:33.917767Z

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Observation 8b5f7984-5bc2-4ce7-9e5a-ca6645728216 · outbound

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

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Learning in Mean Field Games: A Survey

Reference 26

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This paper cites Cardaliaguet, F.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Cardaliaguet, F

Reference 27

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Observation aa717685-7522-4400-b16e-9317d325ada3 · outbound

This paper cites Generalization in mean field games by learning master policies,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Generalization in mean field games by learning master policies,

Reference 28

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Observation c9151804-421f-4a6f-8d98-d4acac624266 · outbound

This paper cites Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Population-aware Online Mirror Descent for Mean-Field Games by Deep Reinforcement Learning

Reference 29

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This paper cites Computing approximate equilibria in sequential adversarial games by exploitability descent,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Computing approximate equilibria in sequential adversarial games by exploitability descent,

Reference 30

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This paper cites Leverage the average: an analysis of kl regularization in reinforcement learning,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Leverage the average: an analysis of kl regularization in reinforcement learning,

Reference 31

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Observation 1a685fed-3b6f-411f-8cdf-6d1271ba6704 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Human-level control through deep reinforcement learning,

Reference 32

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Observation 412a88bf-3e9c-4c31-b144-30b849934a8b · outbound

This paper cites Prioritized Experience Replay.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Prioritized Experience Replay

Reference 33

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This paper cites Overcoming catastrophic forgetting in neural networks,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Overcoming catastrophic forgetting in neural networks,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:33.622270Z

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Observation 88100299-774f-47ab-93f8-50a15718cdaf · outbound

This paper cites Mean field games with common noise,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Mean field games with common noise,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:33.521700Z

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Observation bb4c30b8-c5e7-4989-9635-bf16f2ea5a52 · outbound

This paper cites Training Larger Networks for Deep Reinforcement Learning.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Training Larger Networks for Deep Reinforcement Learning

Reference 36

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Observation 93a6989a-cec1-4ee2-92da-d8e40595e8b5 · outbound

This paper cites Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint

Reference 37

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Source-reported events for the cited work

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Observation 84fc1f63-73ea-4269-96d0-fad270f257e1 · outbound

This paper cites Control of McKean– Vlasov dynamics versus mean field games,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Control of McKean– Vlasov dynamics versus mean field games,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:33.438056Z

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Observation 7e53002c-cff0-401b-8747-ab404dde84a0 · outbound

This paper cites Linear- quadratic mean field games,.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning Linear- quadratic mean field games,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:33.417416Z

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Observation 2cff5988-d999-40f8-985e-5f210bce5c86 · outbound

This paper cites This set comprises 10 distributions originating from fixed points, 10 following Gaussian distributions, and 10 distributed across random points.

Population-aware Online Mirror Descent for Mean-Field Games with Common Noise by Deep Reinforcement Learning This set comprises 10 distributions originating from fixed points, 10 following Gaussian distributions, and 10 distributed across random points

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T16:38:33.295749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

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