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Paper Citation Record · LEDGER

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2606.25526.

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

pith.paper-citation-record.v1
2606.25526 v1

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measured 42 of 42 reference resolution

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Reference resolution

42 of 42 outbound references displayed

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Outbound references

Observation 6b45067e-eff9-4101-a366-75840814ead9 · outbound

This paper cites In: International Conference on Machine Learning, pp.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Machine Learning, pp

Reference 1

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This paper cites Proximal Policy Optimization Algorithms.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 2

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This paper cites In: International Conference on Learning Representations (2022).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Learning Representations (2022)

Reference 3

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Observation 202a086b-79e2-43eb-a267-286f5187da70 · outbound

This paper cites The Journal of Machine Learning Research21(1), 7234–7284 (2020).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning The Journal of Machine Learning Research21(1), 7234–7284 (2020)

Reference 4

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Observation c70f578c-41db-43cd-a757-e387554a43c7 · outbound

This paper cites Advances in neural information processing systems30(2017).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in neural information processing systems30(2017)

Reference 5

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This paper cites Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Reference 6

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This paper cites Advances in Neural Information Processing Systems35, 24611–24624 (2022).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in Neural Information Processing Systems35, 24611–24624 (2022)

Reference 7

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This paper cites Advances in neural information processing systems33, 5527–5540 (2020).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in neural information processing systems33, 5527–5540 (2020)

Reference 8

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This paper cites In: International Con- ference on Learning Representations (2022).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Con- ference on Learning Representations (2022)

Reference 9

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This paper cites In: International Conference on Machine Learning, pp.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Machine Learning, pp

Reference 10

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This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: Proceedings of the AAAI Conference on Artificial Intelligence, vol

Reference 11

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This paper cites In: International Conference on Learning Representations (2019).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Learning Representations (2019)

Reference 12

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This paper cites A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity

Reference 13

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This paper cites Advances in Neural Information Processing Systems35, 16509–16521 (2022).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in Neural Information Processing Systems35, 16509–16521 (2022)

Reference 14

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This paper cites In: Proceedings of the 40th International Conference on Machine Learning, vol.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: Proceedings of the 40th International Conference on Machine Learning, vol

Reference 15

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This paper cites In: International Conference on Learning Representations (2022).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Learning Representations (2022)

Reference 16

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This paper cites Advances in Neural Information Processing Systems34, 12208–12221 (2021).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in Neural Information Processing Systems34, 12208–12221 (2021)

Reference 17

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This paper cites In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp

Reference 18

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This paper cites Advances in Neural Information Processing Systems34, 26437–26448 (2021).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in Neural Information Processing Systems34, 26437–26448 (2021)

Reference 19

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This paper cites Advances in neural information processing systems32(2019).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in neural information processing systems32(2019)

Reference 20

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This paper cites Neural PPO-Clip Attains Global Optimality: A Hinge Loss Perspective.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Neural PPO-Clip Attains Global Optimality: A Hinge Loss Perspective

Reference 21

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This paper cites In: Proceedings of the Nineteenth International Conference on Machine Learning, pp.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: Proceedings of the Nineteenth International Conference on Machine Learning, pp

Reference 22

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Observation 3cc91ded-77f3-47a8-ab08-45cda041c5ac · outbound

This paper cites In: Proceedings of the 34 AAAI Conference on Artificial Intelligence, vol.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: Proceedings of the 34 AAAI Conference on Artificial Intelligence, vol

Reference 23

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This paper cites Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks

Reference 24

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This paper cites Transactions on Machine Learning Research (2023).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Transactions on Machine Learning Research (2023)

Reference 25

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Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning FACMAC: Factored Multi-Agent Centralised Policy Gradients

Reference 26

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Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning The StarCraft Multi-Agent Challenge

Reference 27

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This paper cites Journal of Machine Learning Research25(32), 1–67 (2024).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Journal of Machine Learning Research25(32), 1–67 (2024)

Reference 28

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This paper cites Proceedings of the national academy of sciences114(13), 3521–3526 (2017).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Proceedings of the national academy of sciences114(13), 3521–3526 (2017)

Reference 29

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Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning IEEE Transactions on Neural Networks and Learning Systems (2023)

Reference 30

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Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Multi-Agent Constrained Policy Optimisation

Reference 31

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This paper cites In: International Conference on Machine Learning, pp.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Machine Learning, pp

Reference 32

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This paper cites In: International Conference on Machine Learning, pp.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: International Conference on Machine Learning, pp

Reference 33

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Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in neural information processing systems 29(2016)

Reference 34

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Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Advances in Neural 35 Information Processing Systems34, 13458–13470 (2021)

Reference 35

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Observation b5584e8d-19dd-4c61-8afd-9e0ae4990794 · outbound

This paper cites In: The Eleventh International Confer- ence on Learning Representations (2023).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: The Eleventh International Confer- ence on Learning Representations (2023)

Reference 36

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Observation 54fc2b56-a0ac-4865-85e6-66d9825432f9 · outbound

This paper cites In: Proceed- ings of the 17th International Conference on Autonomous Agents and MultiAgent Systems.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning In: Proceed- ings of the 17th International Conference on Autonomous Agents and MultiAgent Systems

Reference 37

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Observation f2109b79-44ed-46e2-b8c9-20eb78192180 · outbound

This paper cites A unified view of entropy-regularized Markov decision processes.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning A unified view of entropy-regularized Markov decision processes

Reference 38

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metadata mismatch
local_arxiv, observed 2026-07-04T19:30:07.604839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 25b37762-775e-409e-89b2-322c9752f19e · outbound

This paper cites Mathematical programming 198(1), 1059–1106 (2023).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Mathematical programming 198(1), 1059–1106 (2023)

Reference 39

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Observation 48fc81a1-f672-4791-82d0-21e6ab3f41fd · outbound

This paper cites SIAM-Society for Industrial and Applied Mathematics, Philadelphia, PA, USA (2017).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning SIAM-Society for Industrial and Applied Mathematics, Philadelphia, PA, USA (2017)

Reference 40

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Observation 1276ca49-ae62-47a4-86a5-8145d237f1a2 · outbound

This paper cites The Journal of Machine Learning Research22(1), 4431–4506 (2021).

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning The Journal of Machine Learning Research22(1), 4431–4506 (2021)

Reference 41

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source=pdf_text observed=2026-06-25T21:17:28.832301Z digest=sha256:2857657486885faf384ad9fc8f529666a06918b77eb605f3381d057b647e2180

Observation d22bef29-31a7-4ef7-a9c1-3be7f32bb2cc · outbound

This paper cites Equivalence Between Policy Gradients and Soft Q-Learning.

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning Equivalence Between Policy Gradients and Soft Q-Learning

Reference 42

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local_arxiv, observed 2026-07-04T19:30:07.612436Z

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Pith citing papers

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