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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.132675Z digest=sha256:8a0cc4a35e292a9e82dbc2ab727b66b7c1d50f18fedebaecf5a776c0ea5fb235

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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source=arxiv_source observed=2026-08-11T14:19:32.141863Z digest=sha256:b4a8dbf8a618224bbda6b428f80505cefe1c730f9e01cb04525c67abfcb74299

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.146571Z digest=sha256:b353fa2a32b49d2985b9fd6bc14c7803c2c5afed643ade4133cc24671c349b84

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:d7411d03715399161d211b1cfcf27c734b084f9641bc0fde5dca0fe1c094084d

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.155779Z digest=sha256:8ae7f8dca8dd22bb31551456ecc73bfaae29521d0a980e3eff532014419b804b

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
verified exact
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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.160038Z digest=sha256:e907332511eb8342ca49ccc27687a10b2f4c77653b836f3b89543afcadbfcc5f

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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verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.165638Z digest=sha256:8ae956dce8d65e891454670288c75866a76f348ad1b2f7b8f33e66ea47bfe9db

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

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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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.169923Z digest=sha256:1a1086a1797e25db233ae7d469674f91c576731a9b60175635b646865b1bfbee

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.174444Z digest=sha256:f055d0d3b275c3b1ba2535c813135c5fd43babd02e50d74578b1b5751943ee3b

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.178197Z digest=sha256:e758b6c44adca7f4d5d77bab1fe88831e8258e8d4fddf615d99a802276ca9195

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=sha256:4229f803ade52a66550341aee516848fae114d7d9150aed04ad2552e39ec15b9

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
verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.186182Z digest=sha256:cdcb63e1c27ce8156ccc12e879a2f217c64e7cadd96b5d346bf066bad4d6ecb0

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.189687Z digest=sha256:32d5025527ccd1b9e2e3709fed6862d272bb07c7aabcd22e6bd82514c3482e0d

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
verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.193039Z digest=sha256:b52e4bc441faf40ff571b7ca742359818ef5a94faea62600a42be7394edb3317

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.196844Z digest=sha256:8dc7399441951e79eeb5fc093c781ef78114b77fb52849391bf6fcd6c01bd024

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

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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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.201008Z digest=sha256:1cc210bd8f831fc6bc16faebf534ee78b61c3da5474874e390a5f2a4171cca69

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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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.205701Z digest=sha256:94fbf705320358409e1ed5a5fe2e852f48a57a88d3d3bbcf45db57971af53d01

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

Resolution
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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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.209983Z digest=sha256:773fdedd7d9f029c666cd35d53ae5b2ac3d7b4ee4bcdc9a8140f6fc5ab7adb25

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:e22c2a91137d6194d8f7fcddad6e01609ded4902157508d66214d74ef2479546

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.217492Z digest=sha256:52253013a40ab24773b6e1a00a15bd959dfd14dbbe6153ad0cfdc26a61e7050e

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=sha256:13fe7a67032af0351cf875bea28312ea09ac6ad5154fb44ce56a84e10d962c2f

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=sha256:12fb8bf34b9a1ebf1eda19e3e5fa0d2226b963f00a76eed26554762404563e2b

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

Resolution
verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.230577Z digest=sha256:d9892f734110607ee036580e0d953c7278b388402d19ce7dfdbaae9da41ace21

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.234622Z digest=sha256:580b0da4c81e3eb88b0652824e3a5feb2380878a9df4de06baf2a8ac76ca1fd1

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.238823Z digest=sha256:449961958853406c743ed6ad16d0939ee061ed860aa35d22bebe2c46bbcef625

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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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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.242933Z digest=sha256:993433dbaa83590629c082a972495a364185e0b204acdd8a491eda757d245645

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.247371Z digest=sha256:5e3870c498eb061f10546891d1df35d00af0b35894377d0e2e597efd0005d68a

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.251536Z digest=sha256:7d418523356609c318c724ce854012a14a251e9d6b62e6d860918e321bf46735

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.256195Z digest=sha256:473a8ebbc17f1d67fef6473bdc48ec474598bb780df87817ca1ce449277b6360

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

Resolution
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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.260667Z digest=sha256:e8981af7dacee0a0cc8b5ba79fa902370e9d3ddf7100345d69c53b3ed692e93c

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.264747Z digest=sha256:75adf14172ea3f6b44b0723fc8a7d40741b29b3851e39369e9b1d8f315614c07

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:a588dd4bc169058c1da5788cb70c95a979dd9c7a0b63bfff5ff90bc6620041ea

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=sha256:23c068ee1900ba29a299cc717413442d30ed98878a755ecb728c32d8f9133deb

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.277737Z digest=sha256:54b63231cd3ab0211e96da1e63b5b47624887f2c87a4d806895fb3435294c3b0

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=sha256:6100c7115f4223ea0ab0a85b701d86927548377ba20510317c4e12af13d19171

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.285049Z digest=sha256:029ce6ceb53d4e6eab76e919155d52877e48d2e520f05a77548fee2e64c4e35e

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

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source=arxiv_source observed=2026-08-11T14:19:32.288596Z digest=sha256:ce402228c29562de28f16c494c66f4ef9c036a187b77789fd545f30a5c79a46d

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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no resolver link, observed 2026-08-11T14:19:32.292618Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.292618Z digest=sha256:1dbef587d7de0b8f283097b19e26249c81a6b5dfd9c68c4214ead18f3c243171

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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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:a1792b945c2234ebf86fe7acd6cfbcb67c1207bcd0b7e51def4a4384c685dd41

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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.300716Z digest=sha256:6fe67fc7280c7f4a19df5555ecf484db053cc7709167db68d1eed510c0a0a9f7

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.305272Z digest=sha256:4c354cd14f857025a7635c774d9d2dbd63892628d68a242f2c9a490a5b4df04d

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:bfea5041924ccd1c724ce7d77ee2fb30ed673e79bbfe0c179737a93208b5fb2b

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.313924Z digest=sha256:3c1620d7b8432ce111e7be6917fbdb798bc00b86cec81f1c544376253c5d2297

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.318204Z digest=sha256:4c93460b03e11de1634deaaa8e483516ac26d86d78cd65db57f0829623ac8b3d

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.322237Z digest=sha256:14c304727a7ee1a1468a2e49625d184fdab654b5f5557d5b3f06398712b37726

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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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=sha256:897afce869e92a439a887e8bb18e1eaa2db561da942ddcd0efa640ce3bbc3eb5

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.329928Z digest=sha256:0b86a63c0bbf37e7886b8cc9dd5a879d34b531b709cd8adc0fd1910f603d5927

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.333972Z digest=sha256:4479af12da8198b910c5dacd135c77f53a0f0f35082e48a4e4156c1d68054afb

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

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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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.337904Z digest=sha256:1fd18fcb860ed6e3aab1536ffaeda415fcb22f2fd66c1ee2edb5a3582f11acdc

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.341778Z digest=sha256:e23fd8fb7d8d10b564303e364b923f425fb42588760945b51752a06e58030c9d

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:19:32.345482Z digest=sha256:01edbe6e17cec16e37f0d51dbaa8867a4c8e2d4590a65b7996b3ed9d069ff7e3

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

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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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.349609Z digest=sha256:d232e6c6a4131d94debe2e90e260431fb4f4a211be2cdb7a6e0634d0e1e881f8

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 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T14:19:32.354140Z digest=sha256:41a04a45aaa188212c1bf91867c50ba7b128cb0f9cfc7980bc2a5f714d921fc7

Pith citing papers

No inbound Pith citation observations are available.