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Paper Citation Record · LEDGER

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing

As of 12 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2412.12326.

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

pith.paper-citation-record.v1
2412.12326 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:19:32.354140Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

53 of 53 outbound references displayed

  • verified exact11
  • verified fuzzy20
  • unresolved20
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5a7ea804-97a6-4924-9d4b-dfdd9afc40a8 · outbound

This paper cites Albrecht and Peter Stone.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Albrecht and Peter Stone

Reference 1

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no resolver link, observed 2026-08-11T14:19:32.132675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.132675Z digest=sha256:7cc12e39748df52a5dcf1c32b1e4ffedf59b471f0c7148e52bf0b6894f14e3d1

Observation d6df5b9a-de0b-4e37-83ff-51b81f9b4767 · outbound

This paper cites Giannakis, and Tamer Basar.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Giannakis, and Tamer Basar

Reference 2

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no resolver link, observed 2026-08-11T14:19:32.141863Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.141863Z digest=sha256:3a8aa91c04955103553a5e821a1ed6c533775a855dff3e73a134b08a19dacc2b

Observation 53e99242-bb3d-4fc3-90e8-d33302965c58 · outbound

This paper cites Formal Contracts Mitigate Social Dilemmas in Multi-Agent RL.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Formal Contracts Mitigate Social Dilemmas in Multi-Agent RL

Reference 3

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no resolver link, observed 2026-08-11T14:19:32.146571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.146571Z digest=sha256:0be35ce9ce2c59fe3b6d87fa815218f897f258363c52338d28c2a57f660e6c0d

Observation f73bb17c-cb3d-484d-85aa-6c18ffad38db · outbound

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

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Multi-agent Reinforcement Learning for Networked System Control

Reference 4

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no resolver link, observed 2026-08-11T14:19:32.151157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.151157Z digest=sha256:52ed43387f462be4aca75601f25081a82d2d00f3e8e36840bb1c0777ef2b3045

Observation ee923d9b-fa2c-48d9-8cdc-d9f2c0bfa878 · outbound

This paper cites Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Multi-Agent Deep Reinforcement Learning for Large-Scale Traffic Signal Control

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:19:34.065149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.155779Z digest=sha256:e1c7ad29853f040917345d488d9ae49ac94479eb4d3d41e0a8f680685747ee1d

Observation e093aac0-3e7a-4bf2-86f1-c0433a3e1a49 · outbound

This paper cites Scalable Model-based Policy Optimization for Decentralized Networked Systems.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Scalable Model-based Policy Optimization for Decentralized Networked Systems

Reference 6

Resolution
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local_arxiv, observed 2026-08-11T14:19:33.666937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.160038Z digest=sha256:18d72d2accd3025e248f3d4f9ef6eecf8745821da4311f111c3ca1ba26dd28a0

Observation 184b8f26-1249-4924-9360-0ddeed157b97 · outbound

This paper cites Torr, Pushmeet Kohli, and Shimon Whiteson.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Torr, Pushmeet Kohli, and Shimon Whiteson

Reference 7

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raw_fallback, observed 2026-08-11T14:19:34.051501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.165638Z digest=sha256:5cdd28c6bbf191c539a9ac110a46ea95b979d1c982d8d8d98a72a4faf27fa5e0

Observation 52bab823-68f4-4418-911d-d70b3ab505c5 · outbound

This paper cites Brown, Erin E.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Brown, Erin E

Reference 8

Resolution
verified exact
raw_fallback, observed 2026-08-11T14:19:33.647190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.169923Z digest=sha256:71e221c616adfe6eab27f302ddb3561c0f4b130da2782e491ca973461203db8c

Observation dc381d80-4b83-4486-af76-3e032aadb1c5 · outbound

This paper cites Hauser, Christian Hilbe, Krishnendu Chatterjee, and Martin A.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Hauser, Christian Hilbe, Krishnendu Chatterjee, and Martin A

Reference 9

Resolution
verified exact
doi, observed 2026-08-11T14:19:32.463013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.174444Z digest=sha256:245f1965a82000fd3b7da307804914768b7b7614e3a12b5509d965cb1b0f6817

Observation ac7b753b-4e33-4bb3-8ab8-ed7ec8fdefc5 · outbound

This paper cites Opponent modeling in deep reinforcement learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Opponent modeling in deep reinforcement learning

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.178197Z digest=sha256:414b879703ad422e6c213ea425e2441873626d2c0dfc971a6bce5db2a5c312b2

Observation 760e2073-ade7-4536-bfac-b455e2c3f1d4 · outbound

This paper cites Importance-Aware Message Exchange and Prediction for Multi-Agent Reinforcement Learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Importance-Aware Message Exchange and Prediction for Multi-Agent Reinforcement Learning

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.182470Z digest=sha256:7bb0b041cf7e91f23205c52d78c2fc598d1d472770b67e91712ee7c568c2ff4c

Observation e7553d3d-d35c-4614-abe7-639606192cd3 · outbound

This paper cites Leibo, Matthew Phillips, and Karl Tuyls.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Leibo, Matthew Phillips, and Karl Tuyls

Reference 12

Resolution
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raw_fallback, observed 2026-08-11T14:19:34.026446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.186182Z digest=sha256:82910e71faf634eccb975290fb857fbe5a55602efae97ff803b115a4e415e76c

Observation 98f8b06a-3bbf-483e-9f2a-9b1e00076be1 · outbound

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

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Actor-attention-critic for multi-agent reinforcement learning

Reference 13

Resolution
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raw_fallback, observed 2026-08-11T14:19:34.013000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.189687Z digest=sha256:1cb307aabd9c9daa2f91b4d6080e265cfb1fb28a30cbc7a63486ec3b17529eb0

Observation 0a14c871-ea27-4ac3-a2eb-f6f9e0878c92 · outbound

This paper cites Ortega, D.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Ortega, D

Reference 14

Resolution
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raw_fallback, observed 2026-08-11T14:19:33.999579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.193039Z digest=sha256:be3a4e6340bb7c1ddb1192a6d03a21e068365da49464a80aa6b1affcf65cf120

Observation 8de08f22-5822-486d-bd59-6d72c3f0fcf4 · outbound

This paper cites I2Q : A Fully Decentralized Q-Learning Algorithm.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing I2Q : A Fully Decentralized Q-Learning Algorithm

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.981781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.196844Z digest=sha256:a85f7a5940abf71404b515a0d8a0762df04e42c6dc791e825f0d7cc31decb628

Observation a82aa75a-7150-45f9-a024-0b0d5acb2651 · outbound

This paper cites Hierarchical and Stable Multiagent Reinforcement Learning for Cooperative Navigation Control.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Hierarchical and Stable Multiagent Reinforcement Learning for Cooperative Navigation Control

Reference 16

Resolution
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raw_fallback, observed 2026-08-11T14:19:33.488755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.201008Z digest=sha256:538d99b85fff4830e41487b307d6fb7f0e53252f776411322be218879581e799

Observation b5291ebf-3136-4084-8f3a-5482b3e1442a · outbound

This paper cites Communication in Multi-Agent Reinforcement Learning: Intention Sharing.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Communication in Multi-Agent Reinforcement Learning: Intention Sharing

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.205701Z digest=sha256:d1e41ab15f60ce82b56c3944de3d4aa831fb6d1fd7e8fe8233ecb186d4ca555b

Observation 00e82d2f-ba0b-442b-a386-aae343c4d63f · outbound

This paper cites SOCIAL DILEMMAS: The Anatomy of Cooperation.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing SOCIAL DILEMMAS: The Anatomy of Cooperation

Reference 18

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raw_fallback, observed 2026-08-11T14:19:33.950745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.209983Z digest=sha256:340144221dc5ced2f50301ac31a32c036c2d48b6f3aad71d5fd148ddf273cfa2

Observation 42593a57-b929-4530-a7a5-8a71ba40a57c · outbound

This paper cites Communication-Efficient and Federated Multi-Agent Reinforcement Learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Communication-Efficient and Federated Multi-Agent Reinforcement Learning

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.213587Z digest=sha256:ba47865f9fbac621f805639aec7f6cd747b9b8a3ce71882765a662bfcf31d10b

Observation b0110ca2-ac21-42d5-b942-bc523e125d5b · outbound

This paper cites Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Trust Region Policy Optimisation in Multi-Agent Reinforcement Learning

Reference 20

Resolution
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raw_fallback, observed 2026-08-11T14:19:33.938355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.217492Z digest=sha256:1727c24c690e12f5ca6c350dbba97a9451e6283b80ccd938b76ff573c568baa7

Observation f9289c9c-adb0-4be8-922b-f9758a912f85 · outbound

This paper cites Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge IoT.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge IoT

Reference 21

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.222122Z digest=sha256:35d564177b76af0bc444847171b83b8755af71e54bd194a2f66ad1c6b3ccb508

Observation cf49bacf-c726-4402-8980-8a35d08fea4e · outbound

This paper cites Multi-agent Reinforcement Learning in Sequential Social Dilemmas.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Multi-agent Reinforcement Learning in Sequential Social Dilemmas

Reference 22

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source=arxiv_source observed=2026-08-11T14:19:32.226247Z digest=sha256:303fcab3b3fe92647e33dc394d6b4ee20d5081e7e43a36e78bb19b305deddf0d

Observation 58b8e183-0e69-45a0-abca-4f1e3a63c28d · outbound

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

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Multi-agent actor-critic for mixed cooperative-competitive environments

Reference 23

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raw_fallback, observed 2026-08-11T14:19:33.925292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.230577Z digest=sha256:dfc050ffb20737807103ccd320cd29b137276a89d87f16a05570f4a3083401c8

Observation dba09fe6-56d9-4946-b472-ce7ba02e9e8f · outbound

This paper cites Learning dynamics in social dilemmas.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Learning dynamics in social dilemmas

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.911359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.234622Z digest=sha256:d0fbdfc8a2b9896e1699e40b55fc53c7274feaf289b1543f2855ec09ab51443d

Observation 451e8bd8-9595-4d98-886a-105c43fa5d13 · outbound

This paper cites Milinski, D.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Milinski, D

Reference 25

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verified exact
doi, observed 2026-08-11T14:19:32.449490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.238823Z digest=sha256:610093b69ef903b7738662a167dad36d90015ed234f92278084e797d66bf4867

Observation 1245ba5f-cebe-4dc1-bebe-52bfbac33288 · outbound

This paper cites Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability

Reference 26

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metadata mismatch
raw_fallback, observed 2026-08-11T14:19:33.229751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.242933Z digest=sha256:19f476062aabdbb187d15235f8d07e688a50bdb3c3ac46c58e8a557b45940c23

Observation 578eef1a-158f-4853-a9c0-6f6dc716daf4 · outbound

This paper cites an unresolved cited work.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Unresolved cited work

Reference 27

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verified exact
doi, observed 2026-08-11T14:19:32.434846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.247371Z digest=sha256:b981cebe1675a6ae7004279a3cb4189919ecdff3b4cce522439ec1e541d172d9

Observation 9d47a5e9-ccd3-494b-9f12-172ef710ca86 · outbound

This paper cites Schroeder de Witt, Pierre Alexandre Kamienny, Philip H.S.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Schroeder de Witt, Pierre Alexandre Kamienny, Philip H.S

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.896602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.251536Z digest=sha256:490595de14ad46daf5542811872654fa658e4e81722ee6c797c9556cfd3a8b8e

Observation c5c93bb0-e2a8-45f5-bdb4-139c47c3f6a3 · outbound

This paper cites Improving Sample Efficiency of Multi-Agent Reinforcement Learning with Non-expert Policy for Flocking Control.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Improving Sample Efficiency of Multi-Agent Reinforcement Learning with Non-expert Policy for Flocking Control

Reference 29

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.256195Z digest=sha256:a24ab594a16e630e8f4cf4b6463300af243ebe94d921f38a3977bf8f534b7a96

Observation 6d63ad35-e724-4ab4-ae44-d82ef3ebbefb · outbound

This paper cites Trust region policy optimization.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Trust region policy optimization

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.881363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.260667Z digest=sha256:bb19b9d10cd63eafafdd7e55cb8c9a7356703f2c2500cd58e3a3a573c25774c6

Observation 33440bc9-2440-4de8-bfeb-718f759d9b9a · outbound

This paper cites Jordan, and Pieter Abbeel.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Jordan, and Pieter Abbeel

Reference 31

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raw_fallback, observed 2026-08-11T14:19:33.861430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.264747Z digest=sha256:0e2f84fffa1053e455a55b7ea621d4b25034c8fa5612f2ca9425d517174224ea

Observation f8fd5291-cb14-4fa0-9a97-88d330c78d40 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Proximal Policy Optimization Algorithms

Reference 32

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no resolver link, observed 2026-08-11T14:19:32.269152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.269152Z digest=sha256:37f2ae51eb13cef8a4efc6ac69990a64fe738317e56352fc5b5b39e640821d7a

Observation 18ab4e36-db35-40f0-b7e4-8c4559f291c6 · outbound

This paper cites Policy evaluation for reinforcement learning over asynchronous multi-agent networks.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Policy evaluation for reinforcement learning over asynchronous multi-agent networks

Reference 33

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no resolver link, observed 2026-08-11T14:19:32.273844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.273844Z digest=sha256:8a72f6aba1eef57a913afdebe4b9f992e9cb8e0c9d478836ac43e29d6a963799

Observation 2c1e90a3-c93e-42ff-b5e1-578284e3cd04 · outbound

This paper cites Dynamic Collaborative Multi-Agent Reinforcement Learning Communication for Autonomous Drone Reforestation.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Dynamic Collaborative Multi-Agent Reinforcement Learning Communication for Autonomous Drone Reforestation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.847491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.277737Z digest=sha256:93392a9ca3d1151f41c593f41beb13774263f5c6cf8839966faff3ac7088301e

Observation 45f04930-a628-4ff6-91c2-fbd10b76343f · outbound

This paper cites Stankovic, Marko Beko, and Srdjan S.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Stankovic, Marko Beko, and Srdjan S

Reference 35

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no resolver link, observed 2026-08-11T14:19:32.281639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.281639Z digest=sha256:863192a67bc7a344d52ea4c92f8fd6f35d7e0281c1578d094b84d0c1d958c007

Observation f283ca85-a102-479c-a4aa-467ee5138516 · outbound

This paper cites Stankovic, Marko Beko, and Srdjan S.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Stankovic, Marko Beko, and Srdjan S

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.285049Z digest=sha256:2d12cd6e1b65b7b0f1339326cb80f1bd247e075c8615b2c7e475f98e4c632f6e

Observation 7a48e88a-5feb-42c4-92fc-645201acaa17 · outbound

This paper cites Decentralized Policy Optimization.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Decentralized Policy Optimization

Reference 37

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no resolver link, observed 2026-08-11T14:19:32.288596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.288596Z digest=sha256:1757fdeb9556ae800f8f4d35d1eb28f6aac8c974326508cf3375cda4ccf64110

Observation ccb84ab6-98b8-4098-959b-ea53995b484c · outbound

This paper cites an unresolved cited work.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Unresolved cited work

Reference 38

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.292618Z digest=sha256:aa2540f19c570516e76b51051b3943e55091ff83fdfeca2a8c848e4b6279c871

Observation c0b50ea6-9c0c-4f96-a4c6-36b7c6a2bd3b · outbound

This paper cites Trust Region Bounds for Decentralized PPO Under Non-stationarity.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Trust Region Bounds for Decentralized PPO Under Non-stationarity

Reference 39

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unresolved
no resolver link, observed 2026-08-11T14:19:32.296024Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.296024Z digest=sha256:6603166a48ab647ae2bcecb72fd999ec42b87562d2dc1d3bb94dc2969e0f1b6b

Observation 9f9ec162-f738-4c32-a2a3-264539def5e1 · outbound

This paper cites A multi-agent off-policy actor-critic algorithm for distributed reinforcement learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing A multi-agent off-policy actor-critic algorithm for distributed reinforcement learning

Reference 40

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verified exact
doi, observed 2026-08-11T14:19:32.422543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.300716Z digest=sha256:b71272ba630ad6e5dda2496cfcc20c6e2531611f18e0ccc8f65e77680c6ad09f

Observation 998d458f-25d5-4bd9-8e02-2396fae9665b · outbound

This paper cites Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning

Reference 41

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verified exact
local_arxiv, observed 2026-08-11T14:19:32.744828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.305272Z digest=sha256:aa901b100a798dfb5471bf2bbea0d3493d1a0ab3a1cad2468ed1cad24697ddcc

Observation 6fa6032d-d81d-4c0d-a834-df0e9715cd8d · outbound

This paper cites Van Lange, Jeff Joireman, Craig D.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Van Lange, Jeff Joireman, Craig D

Reference 42

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no resolver link, observed 2026-08-11T14:19:32.309855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.309855Z digest=sha256:ad90da46088366fdd5ff2ea2508c2a366f5fe821ca07cd59d44a1672b210ddc0

Observation 246e360d-6409-41c0-9c70-8dc9a273296d · outbound

This paper cites Distributed Reinforcement Learning for Robot Teams: A Review.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Distributed Reinforcement Learning for Robot Teams: A Review

Reference 43

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verified exact
local_arxiv, observed 2026-08-11T14:19:32.725846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.313924Z digest=sha256:c8199b3f403034039cfb5857c1319c0889be782ef5d4c6c3c5c422b7e0deda16

Observation 59257c7e-c13f-4606-b6d3-d270b33acacd · outbound

This paper cites Probabilistic recursive reasoning for multi-agent reinforcement learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Probabilistic recursive reasoning for multi-agent reinforcement learning

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.830886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.318204Z digest=sha256:1da720dd1e6f5e0e5b22adaa9720fe70f5bf943aac9c27f0b521dfc6fe47af33

Observation da6a5814-5cd5-473d-819a-6bfe0afd4a81 · outbound

This paper cites Coordinated Proximal Policy Optimization.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Coordinated Proximal Policy Optimization

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.817061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.322237Z digest=sha256:46330d55fa69a5939ebd791c0afe20f9ff4aee544a94f05b66e95d24c04fa29f

Observation 12273adc-97b8-4a41-981d-9ef80138d6bc · outbound

This paper cites Multi-Agent Reinforcement Learning Aided Intelligent UAV Swarm for Target Tracking.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Multi-Agent Reinforcement Learning Aided Intelligent UAV Swarm for Target Tracking

Reference 46

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unresolved
no resolver link, observed 2026-08-11T14:19:32.326177Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.326177Z digest=sha256:1b03f77d145a5677ba6a0aedf7197573fd75cd1562106f42d6eb747e2e5c0a18

Observation 7ef714b3-833e-4d12-8dd8-e7a2493b65f4 · outbound

This paper cites Learning to Share in Multi-Agent Reinforcement Learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Learning to Share in Multi-Agent Reinforcement Learning

Reference 47

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verified exact
local_arxiv, observed 2026-08-11T14:19:32.642168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.329928Z digest=sha256:866494e71e890a52659fdadea41a4bff31abc3a5a5e19f7ee0ea21f4bf2ae03b

Observation 0a51bcb5-21d6-4958-9b14-673194979588 · outbound

This paper cites Networked Multi-Agent Reinforcement Learning in Continuous Spaces.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Networked Multi-Agent Reinforcement Learning in Continuous Spaces

Reference 48

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no resolver link, observed 2026-08-11T14:19:32.333972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.333972Z digest=sha256:be27f915acb4bd0be7fe5b06bbb53a67cf78d6ef3d29810bb997327b0f94d883

Observation 244bbf76-f167-4774-a66e-25f486e73af7 · outbound

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

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Fully decentralized multi-agent reinforcement learning with networked agents

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.803461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.337904Z digest=sha256:17a8b0a401f439f60854cc645340447cebbb6fe038c52bd63a554e93a9086f65

Observation 65850eb7-d79b-45c2-8674-dcbc5019924d · outbound

This paper cites Finite-sample analysis for decentralized cooperative multi-agent reinforcement learning from batch data.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Finite-sample analysis for decentralized cooperative multi-agent reinforcement learning from batch data

Reference 50

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verified exact
doi, observed 2026-08-11T14:19:32.401711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.341778Z digest=sha256:15b30b16ac20caf50094a5548363ab83ab423d88bcc72ad175129f6db31aeb56

Observation dd37d025-b62d-45f7-b726-8dc8f10fa8b1 · outbound

This paper cites Zavlanos.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Zavlanos

Reference 51

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no resolver link, observed 2026-08-11T14:19:32.345482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.345482Z digest=sha256:1c55aed7e6272b0b77ab393874614c9aec896e2da33ac62245baa6dac80c8550

Observation c1177606-0320-48f5-a837-b8fcde538305 · outbound

This paper cites Distributed policy evaluation via inexact ADMM in multi-agent reinforcement learning.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing Distributed policy evaluation via inexact ADMM in multi-agent reinforcement learning

Reference 52

Resolution
verified exact
doi, observed 2026-08-11T14:19:32.389423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.349609Z digest=sha256:ee59eac67d62c43763842cf48292a61e51194ae1c2c6d33b471278826456dc63

Observation 9a10b1d2-5b6b-4c01-a513-c2059e1cfd70 · outbound

This paper cites A deep Bayesian policy reuse approach against non-stationary agents.

Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing A deep Bayesian policy reuse approach against non-stationary agents

Reference 53

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verified fuzzy
raw_fallback, observed 2026-08-11T14:19:33.789129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.354140Z digest=sha256:0fee2a9b81d9a5cce161dc090f6e21d8c7749d17d8a521a7025b24dcd448e671

Pith citing papers

No inbound Pith citation observations are available.