Paper Citation Record · LEDGER

Power Grid Control with Graph-Based Distributed Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2509.02861.

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

pith.paper-citation-record.v1
2509.02861 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:25:05.332395Z

measured 34 of 34 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

34 of 34 outbound references displayed

verified exact5
verified fuzzy20
unresolved9
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fda6eaed-fd7a-4101-9674-9136ca613be4 · outbound

This paper cites Reinforcement Learning for Electricity Network Operation.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Reinforcement Learning for Electricity Network Operation

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.247153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4d2fd0f-e2b6-479f-8d79-844980af80a3 · outbound

This paper cites Power Grid Congestion Management via Topology Optimization with AlphaZero.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Power Grid Congestion Management via Topology Optimization with AlphaZero

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.250194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31d0cda3-64fc-4b1c-acc7-8f3e9fdaaae5 · outbound

This paper cites Powrl: A reinforcement learning framework for robust management of power networks.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Powrl: A reinforcement learning framework for robust management of power networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.908462Z

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.

Observation 2538cc10-7b4a-439b-8ea2-33697c05a454 · outbound

This paper cites Multi-Agent Reinforcement Learning for Power Grid Topology Optimization.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Multi-Agent Reinforcement Learning for Power Grid Topology Optimization

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:25:05.708783Z

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.

Observation 6187fc70-87d3-4338-95c1-f160acffdab0 · outbound

This paper cites HUGO -- Highlighting Unseen Grid Options: Combining Deep Reinforcement Learning with a Heuristic Target Topology Approach.

Power Grid Control with Graph-Based Distributed Reinforcement Learning HUGO -- Highlighting Unseen Grid Options: Combining Deep Reinforcement Learning with a Heuristic Target Topology Approach

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:25:05.696758Z

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.

Observation 1eb0ddb0-b618-41b6-bdf2-9189b65aa084 · outbound

This paper cites Learning to run a power network challenge: a retrospective analysis.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Learning to run a power network challenge: a retrospective analysis

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.901018Z

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.

Observation acf43c26-c76a-4c46-a42c-fb1b1c352560 · outbound

This paper cites Grid2op: A testbed platform to model sequential decision making in power systems, 2020.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Grid2op: A testbed platform to model sequential decision making in power systems, 2020

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.893726Z

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.

Observation 74ccdbe0-5dd4-43c6-8093-d9e0af03a101 · outbound

This paper cites Multi-agent reinforcement learning: A selective overview of theories and algorithms.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Multi-agent reinforcement learning: A selective overview of theories and algorithms

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.886339Z

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.

Observation 8d1706c9-0166-430c-a842-154dd645b89e · outbound

This paper cites an unresolved cited work.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-05T11:25:05.878147Z

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.

Observation 0b55787f-a830-41b0-b0ac-050e857aed29 · outbound

This paper cites Deep q-learning from demonstrations.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Deep q-learning from demonstrations

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.870559Z

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.

Observation e71d439b-a6b1-4d22-be2f-6258060668aa · outbound

This paper cites Kulkarni.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Kulkarni

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.862846Z

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.

Observation 0348b3ab-1c10-4c8a-9f7c-f47b8b8e53de · outbound

This paper cites Dueling network architectures for deep reinforcement learning.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Dueling network architectures for deep reinforcement learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.855263Z

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.

Observation d2c73560-cf1e-4538-91c8-dddddb52fbe3 · outbound

This paper cites Winning the L2RPN challenge: Power grid management via semi-markov afterstate actor-critic.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Winning the L2RPN challenge: Power grid management via semi-markov afterstate actor-critic

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.847370Z

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.

Observation 0d98dbce-55f2-48c5-9cec-479644a566e3 · outbound

This paper cites Centrally coordinated multi-agent reinforcement learning for power grid topology control.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Centrally coordinated multi-agent reinforcement learning for power grid topology control

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.838460Z

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.

Observation 5ace15bf-8557-46d9-9d25-a5c6a7df2ef8 · outbound

This paper cites Hierarchical Reinforcement Learning for Power Network Topology Control.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Hierarchical Reinforcement Learning for Power Network Topology Control

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:25:05.685264Z

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.

Observation f701f750-c41a-4f81-a0ee-59c973dd8f77 · outbound

This paper cites Expert system for topological remedial action discovery in smart grids.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Expert system for topological remedial action discovery in smart grids

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.830064Z

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.

Observation b8b1a363-1116-47f7-ab25-06765809b579 · outbound

This paper cites Beyond homophily in graph neural networks: Current limitations and effective designs.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Beyond homophily in graph neural networks: Current limitations and effective designs

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.821530Z

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.

Observation 20cec761-a0b9-4f8d-ab55-d8ff9b0fcbf7 · outbound

This paper cites Heterophily-aware representation learning on heterogeneous graphs.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Heterophily-aware representation learning on heterogeneous graphs

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.813536Z

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.

Observation 3921776c-0e2e-4a55-ae25-d404cb970299 · outbound

This paper cites Hinormer: Representation learning on heterogeneous information networks with graph transformer.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Hinormer: Representation learning on heterogeneous information networks with graph transformer

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.805262Z

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.

Observation b35203ef-4921-4ed9-93a5-bce4b1be86e0 · outbound

This paper cites Generalizable graph neural networks for robust power grid topology control.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Generalizable graph neural networks for robust power grid topology control

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.297475Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f976bdc8-4e28-43c3-a5a3-1b8f81e033d8 · outbound

This paper cites Kingma and Jimmy Ba.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Kingma and Jimmy Ba

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.299839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bffd0792-f224-4dde-9685-c0f4c8bdc07f · outbound

This paper cites Rusu, Joel Veness, Marc G.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Rusu, Joel Veness, Marc G

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.792264Z

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.

Observation ddf44986-7e1f-4fa5-a909-20d571a43f82 · outbound

This paper cites Lillicrap, Jonathan J.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Lillicrap, Jonathan J

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.784319Z

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.

Observation 4e0a5609-efaa-4c33-852f-8e5b2198e968 · outbound

This paper cites Reinforcement learning (dqn) tutorial - pytorch, 2024.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Reinforcement learning (dqn) tutorial - pytorch, 2024

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.775567Z

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.

Observation 316480c2-fa82-4b7f-9486-16280f6c52e1 · outbound

This paper cites Reinforcement learning for energies of the future and carbon neutrality: a challenge design.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Reinforcement learning for energies of the future and carbon neutrality: a challenge design

Reference 25

Resolution: verified exact; raw_fallback, observed 2026-08-05T11:25:05.540306Z

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.

Observation ef2a9d4e-85a2-4f08-a409-ce33dc4c0883 · outbound

This paper cites URL https://www.artelys.com/app/uploads/2024/04/White_paper_L2RPN_2023_.pdf.

Power Grid Control with Graph-Based Distributed Reinforcement Learning URL https://www.artelys.com/app/uploads/2024/04/White_paper_L2RPN_2023_.pdf

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.767605Z

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.

Observation c3522421-6d80-4250-a2fe-5b1e22f5357b · outbound

This paper cites Proximal Policy Optimization Algorithms.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.314287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63905465-e982-443d-a476-d9dd1077ef20 · outbound

This paper cites Graph reinforcement learning for power grids: A comprehensive survey.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Graph reinforcement learning for power grids: A comprehensive survey

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.316983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd783d98-f592-4e8f-90fc-84250c2160c4 · outbound

This paper cites A simulation-constraint graph reinforcement learning method for line flow control.

Power Grid Control with Graph-Based Distributed Reinforcement Learning A simulation-constraint graph reinforcement learning method for line flow control

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.759491Z

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.

Observation 2474443e-b36e-4690-8d3e-d9b368ae3a25 · outbound

This paper cites Learning to run a power network under varying grid topology.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Learning to run a power network under varying grid topology

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.750937Z

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.

Observation 1e2b82f9-9b42-4510-a367-a7a4a39dc432 · outbound

This paper cites Active power correction strategies based on deep reinforcement learning -- part I : A simulation-driven solution for robustness.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Active power correction strategies based on deep reinforcement learning -- part I : A simulation-driven solution for robustness

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T11:25:05.742839Z

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.

Observation 15fb5905-c0d7-413c-b606-58a710915724 · outbound

This paper cites Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges.

Power Grid Control with Graph-Based Distributed Reinforcement Learning Optimizing Power Grid Topologies with Reinforcement Learning: A Survey of Methods and Challenges

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-05T11:25:05.363698Z

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.

Observation 83fedaa8-e05c-49d3-a179-b286d5b09f8f · outbound

This paper cites , " * write output.state after.block = add.period write.

Power Grid Control with Graph-Based Distributed Reinforcement Learning , " * write output.state after.block = add.period write

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.329518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f575e9b4-bca3-4384-aabc-484547b3992d · outbound

This paper cites write newline.

Power Grid Control with Graph-Based Distributed Reinforcement Learning write newline

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T11:25:05.332395Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.