Paper Citation Record · LEDGER

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces

As of 17 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2607.18554.

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

pith.paper-citation-record.v1
2607.18554 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:07:45.671697Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

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External citation measurements

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Outbound references

Observation db074900-9149-4f9e-9ff3-efba1aaf7f94 · outbound

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

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Multi-agent reinforcement learning: A selective overview of theories and algorithms,

Reference 1

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Observation 4d0640fd-9165-401e-a914-f4e93c376b17 · outbound

This paper cites Stability constrained reinforcement learning for decentralized real-time voltage control,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Stability constrained reinforcement learning for decentralized real-time voltage control,

Reference 2

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Observation 98d8d835-e27f-40d5-9f1e-f373ce4ec53b · outbound

This paper cites Scalable reinforcement learning of localized policies for multi-agent networked systems,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Scalable reinforcement learning of localized policies for multi-agent networked systems,

Reference 3

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Observation 39abe093-75f4-43d7-bcd1-2ed504277f55 · outbound

This paper cites Scalable reinforcement learning for multiagent networked sys- tems,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Scalable reinforcement learning for multiagent networked sys- tems,

Reference 4

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Observation 9b0bebf4-cc51-4cac-8dcc-91045062ae00 · outbound

This paper cites Multi-agent reinforcement learning in stochastic networked systems,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Multi-agent reinforcement learning in stochastic networked systems,

Reference 5

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Observation 26d11f3e-74f4-45f7-b721-4fbdb9af915f · outbound

This paper cites Global convergence of localized policy iteration in networked multi-agent reinforcement learning,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Global convergence of localized policy iteration in networked multi-agent reinforcement learning,

Reference 6

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Observation a5fd7b01-b3ea-470a-983e-9fb19504aaac · outbound

This paper cites Fully decentralized multi-agent reinforcement learning with networked agents,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Fully decentralized multi-agent reinforcement learning with networked agents,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:44.672839Z

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Observation 380f43a1-8d15-4e7e-a29a-f779e003e649 · outbound

This paper cites Finite-time analysis of dis- tributed td (0) with linear function approximation on multi-agent rein- forcement learning,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Finite-time analysis of dis- tributed td (0) with linear function approximation on multi-agent rein- forcement learning,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:44.749424Z

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Observation 80fce664-357f-49ca-ac5e-0e9859a7e637 · outbound

This paper cites Decentralized online convex optimization in networked systems,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Decentralized online convex optimization in networked systems,

Reference 9

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Observation ff360be4-3fe0-43b1-a6e6-7082e426bde6 · outbound

This paper cites Multi-agent Reinforcement Learning for Networked System Control.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Multi-agent Reinforcement Learning for Networked System Control

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:44.900715Z

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Observation ff10ef29-0db5-445e-b3dd-d0e651b15034 · outbound

This paper cites Random features for large-scale kernel machines,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Random features for large-scale kernel machines,

Reference 11

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Observation 45b6321f-8983-43f4-8e68-0aa60bec6e0b · outbound

This paper cites Random features for ker- nel approximation: A survey on algorithms, theory, and beyond,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Random features for ker- nel approximation: A survey on algorithms, theory, and beyond,

Reference 12

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Observation 0758319c-58e1-4bb2-ae17-8568332d969e · outbound

This paper cites Scalable spectral representations for multi-agent reinforcement learning in network MDPs.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Scalable spectral representations for multi-agent reinforcement learning in network MDPs

Reference 13

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Observation af3c1833-2880-4063-92fd-cfa01126defc · outbound

This paper cites Linear least-squares algorithms for temporal difference learning,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Linear least-squares algorithms for temporal difference learning,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:45.209477Z

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Observation 820e9772-ffdf-4788-abfe-c477b2a7d58c · outbound

This paper cites Technical update: Least-squares temporal difference learning,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Technical update: Least-squares temporal difference learning,

Reference 15

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Observation 9c84af58-9a4d-4e35-8308-b8ae758afa4d · outbound

This paper cites Finite-sample analysis of least-squares policy iteration,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Finite-sample analysis of least-squares policy iteration,

Reference 16

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Observation bf0b56bf-d20b-4ebe-8711-5e4887d30db3 · outbound

This paper cites A finite time analysis of temporal difference learning with linear function approximation,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces A finite time analysis of temporal difference learning with linear function approximation,

Reference 17

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Observation fc623c16-c7c9-42c7-b88d-12c72fc7b6bf · outbound

This paper cites An introduction to matrix concentration inequalities,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces An introduction to matrix concentration inequalities,

Reference 18

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Observation 8a738021-d68d-4b74-aa2f-2c70b18a138e · outbound

This paper cites Vershynin,High-dimensional probability: An introduction with ap- plications in data science.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Vershynin,High-dimensional probability: An introduction with ap- plications in data science

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:45.534618Z

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Observation 9912ec25-11ff-43f0-b13c-6c977f9c24e1 · outbound

This paper cites Optimum bounds for the distributions of martingales in banach spaces,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Optimum bounds for the distributions of martingales in banach spaces,

Reference 20

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Observation 02ba7837-d616-490e-971e-35b18668207b · outbound

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Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Unresolved cited work

Reference 21

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Observation 7dd116c8-5efc-4694-ad44-d110294d6535 · outbound

This paper cites Policy gradi- ent methods for reinforcement learning with function approximation,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Policy gradi- ent methods for reinforcement learning with function approximation,

Reference 22

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Observation f6d9d64c-2c40-4010-a9b0-ec8248b72543 · outbound

This paper cites Lower bounds for non-convex stochastic optimization,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Lower bounds for non-convex stochastic optimization,

Reference 23

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Observation fdf0f9db-840d-4561-9b15-0bcb01c2a9bd · outbound

This paper cites On the theory of policy gradient methods: Optimality, approximation, and distribution shift,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces On the theory of policy gradient methods: Optimality, approximation, and distribution shift,

Reference 24

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

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Multi-agent actor-critic for mixed cooperative-competitive environ- ments,

Reference 25

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Observation 1ac1c5a9-6649-41a3-8111-6a498f25c506 · outbound

This paper cites Counterfactual multi-agent policy gradients,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Counterfactual multi-agent policy gradients,

Reference 26

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Observation 473a9151-3d76-4f46-a4b3-2dbc7785c245 · outbound

This paper cites Actor-attention-critic for multi-agent reinforcement learning,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Actor-attention-critic for multi-agent reinforcement learning,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:45.647674Z

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Observation b786be04-134f-4043-9584-1e38448ba09a · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces The surprising effectiveness of ppo in cooperative multi-agent games,

Reference 28

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This paper cites Near-optimal distributed linear-quadratic regulator for networked systems,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Near-optimal distributed linear-quadratic regulator for networked systems,

Reference 29

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Observation 11be9423-6ad9-4224-baf8-250cb9548d5b · outbound

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Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Network reconfiguration in distribution systems for loss reduction and load balancing,

Reference 30

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Observation 67f10cbf-2aa6-477b-9827-8c23e0c86bdc · outbound

This paper cites The description of a random field by means of conditional probabilities and conditions of its regularity,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces The description of a random field by means of conditional probabilities and conditions of its regularity,

Reference 31

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Observation cb46e0a5-6875-44b3-ba4b-4267b90c209c · outbound

This paper cites Can local particle filters beat the curse of dimensionality?.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Can local particle filters beat the curse of dimensionality?

Reference 32

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Observation dde6708c-d21c-42d2-afc5-192f05407b19 · outbound

This paper cites Mini-batch stochastic approx- imation methods for nonconvex stochastic composite optimization,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Mini-batch stochastic approx- imation methods for nonconvex stochastic composite optimization,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:45.668392Z

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Observation e0bcf005-760d-4027-9f54-2ae8649d016b · outbound

This paper cites Stochastic first-and zeroth-order methods for nonconvex stochastic programming,.

Scalable Policy Optimization for Networked Multi-Agent Reinforcement Learning with Continuous State-Action Spaces Stochastic first-and zeroth-order methods for nonconvex stochastic programming,

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T15:07:45.671697Z

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