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Paper Citation Record · LEDGER

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control

As of 23 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 0 inbound Pith citation observations for arXiv:1908.10577.

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

pith.paper-citation-record.v1
1908.10577 v3

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:45:48.307747Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

68 of 68 outbound references displayed

  • verified exact1
  • verified fuzzy61
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 44a41484-d7ea-45c8-aed5-65f8e740cb89 · outbound

This paper cites Traffic’s mind-boggling economic toll,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Traffic’s mind-boggling economic toll,

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 158320cd-e432-46d0-9b4c-4511dfdc77d9 · outbound

This paper cites Exploring the so- cial learning of taxi drivers in latent vehicle-to-vehicle networks,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Exploring the so- cial learning of taxi drivers in latent vehicle-to-vehicle networks,

Reference 2

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raw_fallback, observed 2026-08-14T10:45:49.694581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation ca5d6be0-3b31-4d7d-8613-d72c4a4959af · outbound

This paper cites Bidirectionally coupled network and road traffic simulation for improved IVC analysis,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Bidirectionally coupled network and road traffic simulation for improved IVC analysis,

Reference 3

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation b12744c8-69d8-45a6-935b-ea46949ff69c · outbound

This paper cites Block simplex signal recovery: Methods, trade-offs, and an application to routing,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Block simplex signal recovery: Methods, trade-offs, and an application to routing,

Reference 4

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raw_fallback, observed 2026-08-14T10:45:49.653950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation e77d8205-b154-4228-bf1d-fd54594b9c02 · outbound

This paper cites Re- grets in routing networks: Measuring the impact of routing apps in traffic,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Re- grets in routing networks: Measuring the impact of routing apps in traffic,

Reference 5

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raw_fallback, observed 2026-08-14T10:45:49.636431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 2db67a4d-9018-47c0-a141-3967aeb8fe6b · outbound

This paper cites Competitive analysis for points of interest,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Competitive analysis for points of interest,

Reference 6

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raw_fallback, observed 2026-08-14T10:45:49.617718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8a0a5991-58fa-4982-869e-4a5c104f5544 · outbound

This paper cites Semi-supervised hierarchical recurrent graph neural network for city-wide parking availability prediction,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Semi-supervised hierarchical recurrent graph neural network for city-wide parking availability prediction,

Reference 7

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raw_fallback, observed 2026-08-14T10:45:49.599939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation acac9a22-9b73-4591-bd7c-f6127aaadedc · outbound

This paper cites Settings for fixed-cycle traffic signals,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Settings for fixed-cycle traffic signals,

Reference 8

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raw_fallback, observed 2026-08-14T10:45:49.583029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:47.992830Z digest=sha256:b3644310d1b7403a0b722152fd052dd90e2b2006cf75f8231ba69081d320c857

Observation 116bbfb8-bd05-4e45-ad03-7199acbd5eef · outbound

This paper cites Traffic network micro- simulation model and control algorithm based on approximate dynamic programming,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Traffic network micro- simulation model and control algorithm based on approximate dynamic programming,

Reference 9

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raw_fallback, observed 2026-08-14T10:45:49.562976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation cf641cb6-6db6-4b76-acc5-b84b2fcd74da · outbound

This paper cites Self-organizing traffic lights: A realistic simulation,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Self-organizing traffic lights: A realistic simulation,

Reference 10

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raw_fallback, observed 2026-08-14T10:45:49.544550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 8fabcb6e-f68e-4779-81ab-84c986d4fcb8 · outbound

This paper cites Intellilight: A reinforcement learning approach for intelligent traffic light control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Intellilight: A reinforcement learning approach for intelligent traffic light control,

Reference 11

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raw_fallback, observed 2026-08-14T10:45:49.528381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.010911Z digest=sha256:b8c764950adfb921491b43c24f79b8232fee4f6e0c459e0de3bdae5f01556844

Observation 893d9b57-5d26-47ed-a97b-72241cebb394 · outbound

This paper cites An experimental review of reinforcement learning algorithms for adaptive traffic signal control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control An experimental review of reinforcement learning algorithms for adaptive traffic signal control,

Reference 12

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raw_fallback, observed 2026-08-14T10:45:49.511907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.015935Z digest=sha256:5b3b8d157b8c390bdfcfd4d45d043d0b923a4459f555ececae8fafd450f2331d

Observation 3308ea27-009f-4402-9be6-dd7969bef892 · outbound

This paper cites Em- bed to control: A locally linear latent dynamics model for control from raw images,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Em- bed to control: A locally linear latent dynamics model for control from raw images,

Reference 13

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raw_fallback, observed 2026-08-14T10:45:49.492347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.021233Z digest=sha256:165c1971254a5df96b770beeb550284c347cebb2cb2e824601de1265dc8dd7e0

Observation 10206968-cff2-4fc7-b8e9-f9090f8e4c57 · outbound

This paper cites A comprehensive survey of multiagent reinforcement learning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control A comprehensive survey of multiagent reinforcement learning,

Reference 14

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raw_fallback, observed 2026-08-14T10:45:49.472637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.026290Z digest=sha256:6319d73311b77d89591558f2f3eeba4a472e436d0ba19116e551a260f96ab366

Observation 2e954b87-ff74-4477-8c95-62185da34279 · outbound

This paper cites Multiagent reinforcement learning for urban traffic control using coordination graphs,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multiagent reinforcement learning for urban traffic control using coordination graphs,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:49.454927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.031103Z digest=sha256:f02fae1249089223ecac1cd4226548b9c3d628bc181d40cd41ff072d7e7c78a4

Observation 37c8acfd-44eb-486b-941a-b3c0023df0d1 · outbound

This paper cites Graph attention networks,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Graph attention networks,

Reference 16

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raw_fallback, observed 2026-08-14T10:45:49.438624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 5c87fc6d-0c41-426e-a445-3258a4955876 · outbound

This paper cites Multiagent reinforcement learning for integrated network of adaptive traffic signal controllers (MARLIN-ATSC): methodology and large-scale application on downtown toronto,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multiagent reinforcement learning for integrated network of adaptive traffic signal controllers (MARLIN-ATSC): methodology and large-scale application on downtown toronto,

Reference 17

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raw_fallback, observed 2026-08-14T10:45:49.420160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 61ea6927-18d5-44c0-bf8f-938cbe1f2718 · outbound

This paper cites Adaptive multi-objective reinforce- ment learning with hybrid exploration for traffic signal control based on cooperative multi-agent framework,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Adaptive multi-objective reinforce- ment learning with hybrid exploration for traffic signal control based on cooperative multi-agent framework,

Reference 18

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raw_fallback, observed 2026-08-14T10:45:49.400181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.046868Z digest=sha256:bdca7601a2c27d18016c54f5e8940bdb491d4eae56fc74a5af5c1f8b37559ce0

Observation b5f95c68-d218-4758-8cc4-9616b0ea28c1 · outbound

This paper cites Reinforcement learning for true adaptive traffic signal control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Reinforcement learning for true adaptive traffic signal control,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.051815Z digest=sha256:7a7371a10c1107f908fd9f7d434436c0d289c6739a253e0aefe389536d26002c

Observation a377488e-7794-4e68-be80-82b70f67d372 · outbound

This paper cites An agent-based learning towards decentralized and coordinated traffic signal control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control An agent-based learning towards decentralized and coordinated traffic signal control,

Reference 20

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raw_fallback, observed 2026-08-14T10:45:49.350592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation bde3929c-a86b-4967-a700-35d44f60eac8 · outbound

This paper cites Reinforcement learning of traffic light controllers adapting to traffic congestion.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Reinforcement learning of traffic light controllers adapting to traffic congestion

Reference 21

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raw_fallback, observed 2026-08-14T10:45:49.329959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 4f791da3-ff3e-486b-b431-847b165fde09 · outbound

This paper cites Reinforcement learning- based multi-agent system for network traffic signal control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Reinforcement learning- based multi-agent system for network traffic signal control,

Reference 22

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raw_fallback, observed 2026-08-14T10:45:49.310553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.066991Z digest=sha256:e29790baf7eb1529a0ec3892e107ce9fb4622720ae41930e846e43019941d573

Observation f5aa3d17-e5c0-4ee5-94ea-9611bf7510b8 · outbound

This paper cites Time critic policy gradi- ent methods for traffic signal control in complex and congested scenarios,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Time critic policy gradi- ent methods for traffic signal control in complex and congested scenarios,

Reference 23

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raw_fallback, observed 2026-08-14T10:45:49.287201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.072508Z digest=sha256:82e2406a9cbde2ae350da1cea13ffb01cfef2f968e739472832220a1c6c7ad95

Observation 313ad637-259a-410d-a15e-323cdb14f51a · outbound

This paper cites Coordinated deep reinforce- ment learners for traffic light control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Coordinated deep reinforce- ment learners for traffic light control,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-14T10:45:49.264735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.078203Z digest=sha256:d95b25ea4fbeb02358cbd6af11a43faff85d23590492415b3a56a4c8296587a0

Observation 83e6ba56-6033-46ad-a548-c2778de42170 · outbound

This paper cites Collaborative multiagent reinforcement learning by payoff propagation,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Collaborative multiagent reinforcement learning by payoff propagation,

Reference 25

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raw_fallback, observed 2026-08-14T10:45:49.245209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

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Observation 7021a4dc-4b01-4d5b-be5b-c7bb0b5354ed · outbound

This paper cites Traffic light control by multiagent reinforcement learning systems,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Traffic light control by multiagent reinforcement learning systems,

Reference 26

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raw_fallback, observed 2026-08-14T10:45:49.225927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.088507Z digest=sha256:80899568c2a31b380841443c0ba70c0c39748472e4864eb65e15538f5b50909f

Observation 595abafc-dc3f-49bb-90fe-97538d30ed89 · outbound

This paper cites Multi-agent reinforcement learning for traffic light control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multi-agent reinforcement learning for traffic light control,

Reference 27

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raw_fallback, observed 2026-08-14T10:45:49.207081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.093399Z digest=sha256:d2b4e25f29cf91d801285193d13584acc9a42312fbae9b940c07d97d22a599cb

Observation 8fd6913a-c948-48ec-8de1-4d8b21f382d9 · outbound

This paper cites Multi-agent deep re- inforcement learning for large-scale traffic signal control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multi-agent deep re- inforcement learning for large-scale traffic signal control,

Reference 28

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raw_fallback, observed 2026-08-14T10:45:49.181539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.098608Z digest=sha256:1aa153398c8291fade90b4f87a385680e33559dbb1cbd6a27649c43a8649c5f6

Observation a6cd2be8-ff6a-44c5-a9ad-aa832f51ccf0 · outbound

This paper cites Presslight: Learning max pressure control to coordinate traf- fic signals in arterial network,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Presslight: Learning max pressure control to coordinate traf- fic signals in arterial network,

Reference 29

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raw_fallback, observed 2026-08-14T10:45:49.164616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.103735Z digest=sha256:feaa9f120dff369433915b9b57d6e2ee1bdb7493e1cc5570b7d5301a0eab82e2

Observation 302f9cb1-03bc-468f-afd1-b68efef2d65b · outbound

This paper cites The max-pressure controller for arbitrary networks of signalized intersections,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control The max-pressure controller for arbitrary networks of signalized intersections,

Reference 30

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raw_fallback, observed 2026-08-14T10:45:49.143211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.108389Z digest=sha256:0bbea754f59a54a57aa76c4620b813defdc41ca5c45096f19ecca53bb8837739

Observation 899a21da-ea05-430e-b4a1-6ee5d784f981 · outbound

This paper cites Traffic signal control based on reinforcement learning with graph convolutional neural nets,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Traffic signal control based on reinforcement learning with graph convolutional neural nets,

Reference 31

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raw_fallback, observed 2026-08-14T10:45:49.124863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.113437Z digest=sha256:d9fa594783d9e5a97f4bce52febed56ff8a3b1f1d32366963b8176ee9306c3be

Observation 2bc5ba23-6388-4fe4-90a4-8cd273ed31f5 · outbound

This paper cites Colight: Learning network-level coop- eration for traffic signal control,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Colight: Learning network-level coop- eration for traffic signal control,

Reference 32

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raw_fallback, observed 2026-08-14T10:45:49.105913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.118649Z digest=sha256:5bddc11664901d774baf7d18f591d69d07d9c50d0a2d1fbbf7d436230678fe13

Observation a88a1682-0eab-41f1-999d-7f07e032d79e · outbound

This paper cites A distributed virtual traf- fic light algorithm exploiting short range V2V communications,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control A distributed virtual traf- fic light algorithm exploiting short range V2V communications,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:49.079331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.123690Z digest=sha256:ecc16ed8aec6992105d5a104a8e94e01815162a8fe644dcc11cabe195a40c69f

Observation f87ca0f3-f27a-4c26-ac7a-271c558b3335 · outbound

This paper cites On the impact of virtual traffic lights on carbon emissions mitigation,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control On the impact of virtual traffic lights on carbon emissions mitigation,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:49.061347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.128459Z digest=sha256:14fef89810845badc37eca61ee2a4f6818bc50d2199066f8716dafc7ae3ba186

Observation 57b1c484-dc73-4cd7-b019-655a3474468a · outbound

This paper cites Cooperative multi- agent control using deep reinforcement learning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Cooperative multi- agent control using deep reinforcement learning,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:49.035416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.133349Z digest=sha256:bd80d4a0a49882536b8642d12d84cfb81efa1e85c960b14507c326fa83324645

Observation 8d32b7d9-1481-47e9-857a-e98295f7d729 · outbound

This paper cites Cooperative multi-agent learning: The state of the art,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Cooperative multi-agent learning: The state of the art,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:49.016351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.137989Z digest=sha256:24db19aed719f5d684ae198d56e97e9e56c34a62e26846b409d9b6250cbf2ce0

Observation bb757b96-b408-45b0-be88-ddc9473ab041 · outbound

This paper cites Learning to communicate with deep multi-agent reinforcement learning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Learning to communicate with deep multi-agent reinforcement learning,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.996019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.143187Z digest=sha256:c39030145395a32a1b27c7c5ee19a3d2eb724f32ee288f6f515ac7c930d78716

Observation 7226767f-784a-4bb0-b45e-a8d32738623f · outbound

This paper cites Learning multiagent communi- cation with backpropagation,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Learning multiagent communi- cation with backpropagation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.974071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.148132Z digest=sha256:eb88597fee33d91dd0dcb4ca9c032c95840a3cd9d3293c3df911ece09d478609

Observation 1eadf582-2121-495d-ac58-62d18de05739 · outbound

This paper cites Soft information for localization-of-things,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Soft information for localization-of-things,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.957328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.153054Z digest=sha256:6e083bde5b5923dd8efd03d85f8b8a9e7986434ebeb1ca846f8535c78beb5ede

Observation 52b8fbc5-bb6d-49fe-9ea2-da65fde188d3 · outbound

This paper cites Network operation strategies for efficient localization and navigation,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Network operation strategies for efficient localization and navigation,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.940415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.157834Z digest=sha256:adc50ebfa46ddc4a1406b85430e7ee6488ee831afbf15f1329c6fd57f1a98ecd

Observation 2fc9a315-37fc-448d-af51-df305f8603f3 · outbound

This paper cites Decen- tralized gaussian filters for cooperative self-localization and multi- target tracking,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Decen- tralized gaussian filters for cooperative self-localization and multi- target tracking,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.918454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.162602Z digest=sha256:62643596cca6031abc4e3e832fd49727d5302e938c60ed412f90be39ddde33c4

Observation 09aa34c3-ff4c-44f1-acf7-0a03a7f44abb · outbound

This paper cites Experiments with cooperative control of underwater robots,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Experiments with cooperative control of underwater robots,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.896127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.167621Z digest=sha256:7b9405ce28775156023e472fa38c3b36b3df8f2ab78e3a5e6500afc23c3bb599

Observation c8d101c7-1ce0-48c0-956a-9636a0ffacb4 · outbound

This paper cites A multiple-goal reinforcement learning method for complex vehicle overtaking maneuvers,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control A multiple-goal reinforcement learning method for complex vehicle overtaking maneuvers,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.878109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.172657Z digest=sha256:916cf22f1b4362d7b17cd1d95d50fb7b70b00d14282ab82c9afa024a190a5ee1

Observation bbd3d813-ed02-4f19-8cbc-32c4539ab0ec · outbound

This paper cites Playing atari with deep reinforce- ment learning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Playing atari with deep reinforce- ment learning,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.859932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.177399Z digest=sha256:e6b49c1596012f34a568dc5574efc4e48746e99edc2a90b76b36c5dd2b78180a

Observation f1ff8fa7-8988-42a3-9ca5-9478e9b2b029 · outbound

This paper cites Multiagent cooperation and competition with deep reinforcement learning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multiagent cooperation and competition with deep reinforcement learning,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.844376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.183496Z digest=sha256:e075e188384d6a0a43e966f2d08e33740a11ec567acb034136a701129144ddf5

Observation 66cab8c5-69ca-4792-9acd-4c172d509005 · outbound

This paper cites Empirically Evaluating Multiagent Learning Algorithms.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Empirically Evaluating Multiagent Learning Algorithms

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:45:48.464842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.188074Z digest=sha256:8ec5cd74e7648d0b2d2cf52ea08b0111390032ce08458d1ec3ac49a6058816f0

Observation e13825ec-a69f-4145-a9a4-3704ec45e4f2 · outbound

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

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multi-agent actor-critic for mixed cooperative-competitive envi- ronments,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.827187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.193268Z digest=sha256:9968517add8d0a492d8912bc54db126874c7b95d182cbd40269c3533c883c560

Observation 2a29b7b3-fea7-49ad-bdee-de3746ca49e7 · outbound

This paper cites Graph convolutional reinforcement learning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Graph convolutional reinforcement learning,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.810673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.198170Z digest=sha256:902d2e14a4a0c52b60f24bb01691a0d0d3a1be5c501dba1b59a73f0482887977

Observation 09bdebba-146f-45f5-8a06-dd77437e6100 · outbound

This paper cites The graph neural network model,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control The graph neural network model,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.793570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.203048Z digest=sha256:55c48bce19b05ea4b178db97f5079eb5dac747d8e58f808eea28bd0faad0a668

Observation 01ed2b8b-4126-473f-89de-d49f295378d0 · outbound

This paper cites Relational inductive biases, deep learning, and graph networks.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Relational inductive biases, deep learning, and graph networks

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-14T10:45:48.208111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:45:48.208111Z digest=sha256:27282bcd5e37d59accdff16b62fbce29aa5a79d21099da91b6285826a57b2770

Observation 5439466d-20c0-42d6-83b2-f6ade85ee7b6 · outbound

This paper cites Interaction networks for learning about objects, relations and physics,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Interaction networks for learning about objects, relations and physics,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.776672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.214636Z digest=sha256:0518ebe67ff0c63e03cc9638a8fa695b95ff401b235e4e334f62e4da3ef6c050

Observation 3ee3df93-23ff-48ea-823d-87a884f7586c · outbound

This paper cites Gated Graph Sequence Neural Networks.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Gated Graph Sequence Neural Networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-14T10:45:48.219469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:45:48.219469Z digest=sha256:ada252b0a31a6b80f7bf25c86402e5eeabc91c872cccd24741a6b8146034995a

Observation 214ed6f1-bcfe-4787-b72a-af5d48f055f5 · outbound

This paper cites Abductive learning: towards bridging machine learning and logical reasoning,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Abductive learning: towards bridging machine learning and logical reasoning,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.754056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.225154Z digest=sha256:3e6f8a954bfd7e42635821e4c36de588cae3fb2786a2e5b9c650b40e2071482e

Observation fcb5b43e-de9f-4fa7-a34a-01d9c8982090 · outbound

This paper cites Neural message passing for quantum chemistry,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Neural message passing for quantum chemistry,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.736076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.229770Z digest=sha256:931686f3b91ac4051392c9447b2d5a927e66927f0e256760ab549d5f2d856b6d

Observation bd291113-b441-45b3-bdd5-f0a93dc3e566 · outbound

This paper cites Nervenet: Learning structured policy with graph neural networks,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Nervenet: Learning structured policy with graph neural networks,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.719439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.234553Z digest=sha256:099fcd7d4464f4a59031cb07388e1eb54485c70861007bf61cea49f0e48e2e24

Observation c08e14b8-a67c-4e23-9b3c-9a722addc514 · outbound

This paper cites Deep reinforcement learning with relational inductive biases,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Deep reinforcement learning with relational inductive biases,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.697677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.239268Z digest=sha256:5edaa37413b96d8c86991f7fcd29010d7b78cbb8849dbb9892d936aacc89792e

Observation f9e2c453-871e-4079-8f92-f4b3a2f2fe51 · outbound

This paper cites Simula- tion and optimization of traffic in a city,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Simula- tion and optimization of traffic in a city,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.675185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.244306Z digest=sha256:ac16df7565a24d07d7ae74c723d868bb75af1cc06024e9c2f160a5e4215bbb42

Observation 773d0900-1cd0-4c6a-8b6f-2e69bd638e8d · outbound

This paper cites Long short-term memory,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Long short-term memory,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.652287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.248893Z digest=sha256:9cee9d9277ae395dca39f04bc9bb55d48406e2e3009a205c5ed5139b880a1a33

Observation 15f7536a-bc79-4e39-8e60-6f937da1d7e2 · outbound

This paper cites Multi-agent reinforcement learning: Independent vs. co- operative agents,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Multi-agent reinforcement learning: Independent vs. co- operative agents,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.623179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.253555Z digest=sha256:78aed777f8b144a46846368d0d94203f9962a9d6619b74bc12387345774df19a

Observation 690c5017-3ee0-4f4b-afe4-f1fb9c1d6b80 · outbound

This paper cites Empirical Evaluation of Rectified Activations in Convolutional Network.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Empirical Evaluation of Rectified Activations in Convolutional Network

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-14T10:45:48.258361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:45:48.258361Z digest=sha256:c9967f0530877cb3a669f710e6d2312777ea3093bd7d81f9c22f6d50e3fe4d4b

Observation 1a35ab8e-4995-4d2f-9506-93ab55193069 · outbound

This paper cites Attention is all you need,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Attention is all you need,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.599597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.265863Z digest=sha256:3535eade1f9e2f687660a4cea4d8af1614aab42c52b02373dab3c427c532d795

Observation f04523d0-ce1a-466b-b8a7-1aac1cb44dea · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-14T10:45:48.270953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:45:48.270953Z digest=sha256:1779dddbb14351a4070ee755beed39f350e002a7320ad57167a47da31afe04d1

Observation fe03e030-8001-41ca-849f-c9abce395f59 · outbound

This paper cites Deep recurrent q-learning for partially observable mdps,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Deep recurrent q-learning for partially observable mdps,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.577534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.276448Z digest=sha256:3e378204368d73d8926b7a00d1f7f15eb82d91956287f65a00d4d368517e2b3c

Observation 6a8e906e-8493-47ee-a6cc-bea68079167a · outbound

This paper cites Memory- based control with recurrent neural networks,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Memory- based control with recurrent neural networks,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.553898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.283368Z digest=sha256:1fb3df683934a43897cc36a2bdbecee74787f5aa30eacdf85ba0b552d6c681fb

Observation f7590608-fac9-45a2-b589-dc30786d5173 · outbound

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

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Human-level control through deep reinforcement learning,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.529343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.288889Z digest=sha256:02a36d4b49898a9717113a17b95626a9e106a539db8813062bd8d1aa18a0ff59

Observation e43ea87e-bda9-41ac-9c5d-7df1cc4dbcc0 · outbound

This paper cites Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:45:48.508432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-14T10:45:48.295717Z digest=sha256:5061999a6dc9e38cbba74622309399bc554e49c0485892442fcd917c456a0956

Observation 25087bb8-7e5d-4700-8a16-1ccb3267559c · outbound

This paper cites Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Delving deep into rectifiers: Surpassing human-level performance on imagenet classification,

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-14T10:45:48.302772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:45:48.302772Z digest=sha256:2ded01c417c9e1cd1d3c8dd93f73d0749440dddf764124e88a9f267a344ee5b4

Observation 0fb11ab9-3f06-48d9-a85e-3ab926d6be2a · outbound

This paper cites Adam: A Method for Stochastic Optimization.

STMARL: A Spatio-Temporal Multi-Agent Reinforcement Learning Approach for Cooperative Traffic Light Control Adam: A Method for Stochastic Optimization

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-14T10:45:48.307747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.