Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-19T11:08:51.426575Z
Paper Citation Record · LEDGER
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage
As of 6 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2506.07548.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
59 of 59 outbound references displayed
- verified exact18
- verified fuzzy38
- unresolved0
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- malformed identifier0
- metadata mismatch3
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 7fa6a324-0853-4ec1-9ecc-abf1cf55bcfd · outbound
This paper cites A survey on multi-agent reinforcement learning and its application.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A survey on multi-agent reinforcement learning and its application
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.176673Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a6a66adf-e6fe-4cc6-8731-f95e7d3f33da · outbound
This paper cites A comprehensive survey on multi-agent reinforcement learning for connected and automated vehicles.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A comprehensive survey on multi-agent reinforcement learning for connected and automated vehicles
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.174462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4264b629-d50d-49ae-bf20-04ab19aea8ee · outbound
This paper cites Marlens: Understanding multi-agent reinforcement learning for traffic signal control via visual analytics.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Marlens: Understanding multi-agent reinforcement learning for traffic signal control via visual analytics
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.373302Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b1ef45a9-d453-4972-8192-06249d9c3230 · outbound
This paper cites Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.552234Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e60134e6-dd69-48da-804b-a7c2cf4701b5 · outbound
This paper cites A survey of multi-agent deep reinforcement learning with communication.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A survey of multi-agent deep reinforcement learning with communication
Reference 6
- Resolution
- verified exact
- doi, observed 2026-05-19T11:12:15.384062Z
Source-reported events for the cited work
correction dated 2024-03-16. Source: crossref record 10.1007/s10458-024-09644-x->10.1007/s10458-023-09633-6:correction, observed 2026-07-11T03:07:50.406185+00:00. This notice travels one citation hop only.
Observation e817814d-60e2-457c-9269-35bdf3f97a70 · outbound
This paper cites Deep reinforcement learning: A survey.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Deep reinforcement learning: A survey
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.159161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e875f140-d7b1-4094-b95b-503a2f59ff12 · outbound
This paper cites Weighted qmix: expanding monotonic value function factorisation for deep multi-agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Weighted qmix: expanding monotonic value function factorisation for deep multi-agent reinforcement learning
Reference 8
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a9961338-6965-436c-a4eb-f5df2bba6ca5 · outbound
This paper cites Episodic multi-agent reinforcement learning with curiosity- driven exploration.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Episodic multi-agent reinforcement learning with curiosity- driven exploration
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.154801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 79164b48-ec60-4a69-9a84-e5c8ae8cc421 · outbound
This paper cites Emu: Efficient episodic memory utilization of cooperative multi-agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Emu: Efficient episodic memory utilization of cooperative multi-agent reinforcement learning
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.152821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1c64f3b7-67a7-4d46-be07-f370a00e785b · outbound
This paper cites A survey of reinforcement learning algorithms for dynamically varying environments.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A survey of reinforcement learning algorithms for dynamically varying environments
Reference 12
- Resolution
- verified exact
- doi, observed 2026-05-19T11:12:15.381754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ba868521-54a0-4eeb-8d17-1215d06026e8 · outbound
This paper cites A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A Survey of Learning in Multiagent Environments: Dealing with Non-Stationarity
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T11:12:15.533776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ecc5c207-bda1-405e-96f9-fc50c19aaaeb · outbound
This paper cites The StarCraft Multi-Agent Challenge.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage The StarCraft Multi-Agent Challenge
Reference 14
- Resolution
- metadata mismatch
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 62209474-2270-4fa6-b4cf-cfd2558de696 · outbound
This paper cites SMACv2: An improved benchmark for cooperative multi-agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage SMACv2: An improved benchmark for cooperative multi-agent reinforcement learning
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.172558Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d81b91bc-55f9-4533-af4b-2bb589c21cc7 · outbound
This paper cites A survey on curriculum learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A survey on curriculum learning
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.144601Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 588abd56-c028-45c3-b2a8-cef14516287d · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T11:12:15.536641Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cc91dc0d-3ddb-4cec-b056-da5754061c71 · outbound
This paper cites Counterfactual multi-agent policy gradients.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Counterfactual multi-agent policy gradients
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.140405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f6b5ba46-8fad-4c5d-a37e-9bc7e13145fa · outbound
This paper cites Monotonic value function factorisation for deep multi- agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Monotonic value function factorisation for deep multi- agent reinforcement learning
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.150809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8457f65e-2143-4303-9cc2-fa357808a64c · outbound
This paper cites Discriminative experience replay for efficient multi- agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Discriminative experience replay for efficient multi- agent reinforcement learning
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.142626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b941258a-95ae-4172-a86d-9435420f5286 · outbound
This paper cites Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T11:12:15.549194Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4278ca5b-09f7-47d7-bb87-c9db5b38ab1f · outbound
This paper cites Dealing with non- stationarity in MARL via trust-region decomposition.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Dealing with non- stationarity in MARL via trust-region decomposition
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.099054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1ca85564-b158-442b-b36b-e271b90f0eb0 · outbound
This paper cites Tackling non-stationarity in decentralized multi-agent reinforcement learning with prudent q- learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Tackling non-stationarity in decentralized multi-agent reinforcement learning with prudent q- learning
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.106247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 05aa0ca2-b337-4907-9b98-f1ac5d0df478 · outbound
This paper cites Dealing with non-stationarity in decentralized cooperative multi-agent deep reinforcement learning via multi-timescale learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Dealing with non-stationarity in decentralized cooperative multi-agent deep reinforcement learning via multi-timescale learning
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.166324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e709aba6-7510-4e62-9d4a-2df09df715b5 · outbound
This paper cites Monotonic improvement guarantees under non- stationarity for decentralized PPO.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Monotonic improvement guarantees under non- stationarity for decentralized PPO
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.133809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e644fa80-0a46-4153-8ad2-698557c5c9f3 · outbound
This paper cites Value-decomposition networks for cooperative multi-agent learning based on team reward.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Value-decomposition networks for cooperative multi-agent learning based on team reward
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.122003Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6bd3e3c6-1887-42a3-b997-db2c04901e0e · outbound
This paper cites QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T11:12:15.515186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c1829183-134b-4ba1-b4b0-18623b4feb9c · outbound
This paper cites Team-wise effective communication in multi- agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Team-wise effective communication in multi- agent reinforcement learning
Reference 28
- Resolution
- verified exact
- doi, observed 2026-05-19T11:12:15.393439Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2b4ab3f2-fa57-4167-879e-eb26ad787282 · outbound
This paper cites Scalable communication for multi- agent reinforcement learning via transformer-based email mechanism.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Scalable communication for multi- agent reinforcement learning via transformer-based email mechanism
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.124547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8f29bd60-ff08-4799-be3c-e5f2ba6cb7c9 · outbound
This paper cites Ac2c: Adaptively controlled two-hop communication for multi-agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Ac2c: Adaptively controlled two-hop communication for multi-agent reinforcement learning
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.129413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 681e70c1-bcf2-40cb-b08d-b11cc9476874 · outbound
This paper cites Communication in multi-agent reinforcement learning: Intention sharing.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Communication in multi-agent reinforcement learning: Intention sharing
Reference 31
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f81c8048-5762-4d14-9818-05604413415f · outbound
This paper cites A sequen- tial multi-agent reinforcement learning framework for different action spaces.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A sequen- tial multi-agent reinforcement learning framework for different action spaces
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.113073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9ec9337a-6685-4716-803a-84c6e66e4d8f · outbound
This paper cites Addressing high-dimensional continuous action space via decomposed discrete policy-critic.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Addressing high-dimensional continuous action space via decomposed discrete policy-critic
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.119805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d9b86bab-2a56-4e04-bbce-07778687e15f · outbound
This paper cites D- marl: A dynamic communication-based action space enhancement for multi agent reinforcement learning exploration of large scale unknown environments.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage D- marl: A dynamic communication-based action space enhancement for multi agent reinforcement learning exploration of large scale unknown environments
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.127042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c368e025-1df5-4fdf-bf91-ecca7d30651e · outbound
This paper cites Cooperative modular reinforcement learning for large discrete action space problem.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Cooperative modular reinforcement learning for large discrete action space problem
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.138372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f2841c80-b544-401a-80df-7fc89409c91f · outbound
This paper cites Exploration in deep reinforcement learning: From single-agent to multiagent domain.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Exploration in deep reinforcement learning: From single-agent to multiagent domain
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.379284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c5014f46-13e1-4b75-a081-c2c7d71e083e · outbound
This paper cites Rethinking exploration and experience exploitation in value-based multi-agent reinforcement learn- ing.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Rethinking exploration and experience exploitation in value-based multi-agent reinforcement learn- ing
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.108434Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6df1a2fa-5992-46c3-9fee-e9eb29b17a3e · outbound
This paper cites Scalable evaluation of multi-agent reinforcement learning with melting pot.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Scalable evaluation of multi-agent reinforcement learning with melting pot
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.117478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 34b8e147-dab5-46a9-b494-dacd214514b8 · outbound
This paper cites Sample-efficient multiagent reinforcement learning with reset replay.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Sample-efficient multiagent reinforcement learning with reset replay
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.131494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 22d7f1f8-5dbf-4f12-ad22-26194c77f6c0 · outbound
This paper cites Self- organized group for cooperative multi-agent reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Self- organized group for cooperative multi-agent reinforcement learning
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.168640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 59a4aafd-66da-44ae-a73e-2bd64e3931bd · outbound
This paper cites Google research football: A novel reinforcement learning environment.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Google research football: A novel reinforcement learning environment
Reference 41
- Resolution
- verified exact
- doi, observed 2026-05-19T11:12:15.375837Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 069fb439-390c-4f54-8954-76a4daa4e3b9 · outbound
This paper cites Pommerman: A Multi-Agent Playground.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Pommerman: A Multi-Agent Playground
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.530792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b443bf14-cb00-4f18-9b96-dbd5f29398b6 · outbound
This paper cites The Neural MMO Platform for Massively Multiagent Research.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage The Neural MMO Platform for Massively Multiagent Research
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.518312Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0c6551ca-620b-4595-be86-ac8754e41ff0 · outbound
This paper cites Benchmarking multi-agent deep reinforcement learning algorithms in cooperative tasks.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Benchmarking multi-agent deep reinforcement learning algorithms in cooperative tasks
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.103922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 51f91da0-7c9b-4f6f-8383-20d752cbdc6e · outbound
This paper cites A survey on multi-agent reinforcement learning and its application.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A survey on multi-agent reinforcement learning and its application
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.101145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8c38fe42-1ce9-4ed0-ba90-1b18238e6998 · outbound
This paper cites A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.539994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 984784e3-839e-4323-bd40-9eabdd7c9020 · outbound
This paper cites A concise introduction to decentralized POMDPs, volume 1.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage A concise introduction to decentralized POMDPs, volume 1
Reference 47
- Resolution
- verified exact
- doi, observed 2026-05-19T11:12:15.386684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 07c6ba2a-f762-4824-a383-bebfcc409986 · outbound
This paper cites Cooperative multi-agent control using deep reinforcement learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Cooperative multi-agent control using deep reinforcement learning
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.115326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 936e4ac7-f1e3-440c-8576-5e3f103348af · outbound
This paper cites Multi agent deep reinforcement learning with deep q-network based energy efficiency and resource allocation in noma wireless systems.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Multi agent deep reinforcement learning with deep q-network based energy efficiency and resource allocation in noma wireless systems
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.179189Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9c452e70-daf3-4043-bac1-14aa5721165a · outbound
This paper cites Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Deep Q-Network Based Multi-agent Reinforcement Learning with Binary Action Agents
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.546177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 115426cf-df8f-4859-b2ac-899cf8841013 · outbound
This paper cites The dynamics of reinforcement learning in cooperative multiagent systems.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage The dynamics of reinforcement learning in cooperative multiagent systems
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.170507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d8cd3f2c-7f03-4ccd-a776-8a524cd3d12e · outbound
This paper cites Centralized training with decentralized exe- cution reinforcement learning for cooperative multi-agent systems with communication delay.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Centralized training with decentralized exe- cution reinforcement learning for cooperative multi-agent systems with communication delay
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.181385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1099799c-3f0b-4b0c-9b86-453c0e31561f · outbound
This paper cites An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage An Introduction to Centralized Training for Decentralized Execution in Cooperative Multi-Agent Reinforcement Learning
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:12:15.521735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d1c7f064-ba8f-4a56-af65-1fa8ab84a91a · outbound
This paper cites The surprising effectiveness of ppo in cooperative multi-agent games.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage The surprising effectiveness of ppo in cooperative multi-agent games
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.163669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9e219d8f-4b50-4b30-95ec-2dc62869b603 · outbound
This paper cites Multi- agent actor-critic for mixed cooperative-competitive environments.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Multi- agent actor-critic for mixed cooperative-competitive environments
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.157090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 91c5ef38-5182-4a1d-982f-3abd5bb0ba93 · outbound
This paper cites Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments
Reference 56
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-19T11:12:15.543253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ae42e91b-1b07-4bc0-b5f3-87bf3624232e · outbound
This paper cites Curriculum learning, in: Proceedings of the 26th Annual International Conference on Machine Learning, Associa- tion for Computing Machinery, New York, NY, USA.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Curriculum learning, in: Proceedings of the 26th Annual International Conference on Machine Learning, Associa- tion for Computing Machinery, New York, NY, USA
Reference 57
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-19T11:12:15.390481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8468a40a-ab0f-4080-921d-7b49b7d06fd8 · outbound
This paper cites Self-paced learning for latent variable models.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Self-paced learning for latent variable models
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.146799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1fe699bd-a495-4950-9b05-d576c0219a83 · outbound
This paper cites Available: https://proceedings.neurips.cc/paper files/ paper/2010/file/e57c6b956a6521b28495f2886ca0977a-Paper.pdf.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Available: https://proceedings.neurips.cc/paper files/ paper/2010/file/e57c6b956a6521b28495f2886ca0977a-Paper.pdf
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.135966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 1d11207a-4075-47ee-afdc-12c95bab9dd2 · outbound
This paper cites TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T11:12:15.524547Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 91b17226-a61a-4b96-ac66-e242b95fd14f · outbound
This paper cites Qplex: Duplex dueling multi-agent q-learning.
Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage Qplex: Duplex dueling multi-agent q-learning
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-19T11:12:16.148694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Pith citing papers
No inbound Pith citation observations are available.