Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing | Paper Citation Record

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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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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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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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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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

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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

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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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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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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

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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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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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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

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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

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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

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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

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:19:33.963658Z

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

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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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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

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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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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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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

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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

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

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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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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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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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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

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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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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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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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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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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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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

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

Reference 38

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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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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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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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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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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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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

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

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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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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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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

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

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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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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 2026-08-11T06:34:44.6726+00:00.

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

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

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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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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

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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

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

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