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Paper Citation Record · LEDGER

Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:1706.02275.

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

pith.paper-citation-record.v1
1706.02275 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:50:49.846524Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • metadata mismatch0

External citation measurements

1015
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d3629bbe-9690-40db-871e-9b35c4075fbb · inbound

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning cites this paper.

A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 15

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verified exact
arxiv_id, observed 2026-05-25T01:55:13.354544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T01:50:35.143626Z digest=sha256:97ff83ad3df4b16c42ed8f06e6a93efb0e7ec1df6ea854a53fcc1832a6ce607a

Observation 69106e65-5a25-49e6-a0f5-cc588a0fe7bb · inbound

Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication cites this paper.

Asynchronous Cooperative Multi-Agent Reinforcement Learning with Limited Communication Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 26

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arxiv_id, observed 2026-05-23T03:35:20.723555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T03:34:58.917609Z digest=sha256:5f37ac485d0027302233843bb0eb6089ad8e1d375d4b1ccd682dc098e334bf4b

Observation 614e1993-0868-4665-8657-63e672d53866 · inbound

Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning cites this paper.

Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 25

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no resolver link, observed 2026-08-08T18:50:49.846524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T18:50:49.846524Z digest=sha256:4ad4f8919da689b244f28434e9ecb212ee6e860936ccf9aa0617b1eeb022c0b5

Observation cb24e9d8-f52d-4578-bb2e-8ea42662a020 · inbound

Agent-Based Decentralized Energy Management of EV Charging Station with Solar Photovoltaics via Multi-Agent Reinforcement Learning cites this paper.

Agent-Based Decentralized Energy Management of EV Charging Station with Solar Photovoltaics via Multi-Agent Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 33

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no resolver link, observed 2026-08-07T14:30:03.788342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:30:03.788342Z digest=sha256:e4e47e15274db41aa3201abb3db60f6123909a255e3848ee2a29a94a711626a1

Observation a4950266-b309-4b29-885c-3877313e1841 · inbound

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications cites this paper.

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 2020

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no resolver link, observed 2026-08-07T14:10:42.258052Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:10:42.258052Z digest=sha256:acba84bc85c8e3495af513c4596775f54a25415222839d6f1bf6c6eff91305d0

Observation 8800fbe1-f64a-4347-86cc-f1b2cb2a1b0d · inbound

Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control cites this paper.

Hold My Beer: Learning Gentle Humanoid Locomotion and End-Effector Stabilization Control Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 63

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no resolver link, observed 2026-08-07T12:38:17.151300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:38:17.151300Z digest=sha256:ed56e8c510e75b0326c024b6eb5a9a08fde35d0b90d9102134313f2e5fade335

Observation 91c5ef38-5182-4a1d-982f-3abd5bb0ba93 · inbound

Overcoming Environmental Meta-Stationarity in MARL via Adaptive Curriculum and Counterfactual Group Advantage cites this paper.

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T11:08:51.426575Z digest=sha256:e508f691e7fcb4a0e51b27b0e2ab1f067ce0fd441425e9bb3bf06ee3c920e26d

Observation 8cb6ef5b-b6ae-4b14-88dd-8d0ea723142f · inbound

A Survey of Multi Agent Reinforcement Learning: Federated Learning and Cooperative and Noncooperative Decentralized Regimes cites this paper.

A Survey of Multi Agent Reinforcement Learning: Federated Learning and Cooperative and Noncooperative Decentralized Regimes Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 41

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no resolver link, observed 2026-08-06T19:19:11.881110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:19:11.881110Z digest=sha256:4cfaf783de580d5cc75e8384a95374a13a12e621f8d80e3858394ad470b2539b

Observation 36e789f5-842b-41d8-a7ae-d20096ea7bf6 · inbound

A Learning Framework For Cooperative Collision Avoidance of UAV Swarms Leveraging Domain Knowledge cites this paper.

A Learning Framework For Cooperative Collision Avoidance of UAV Swarms Leveraging Domain Knowledge Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 16

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no resolver link, observed 2026-08-06T17:29:18.993051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:29:18.993051Z digest=sha256:bd8f2f897c4b65dc95d9d3e2268f5172f41e224a85c2da50a9ea79586327a804

Observation 66b82ebf-efd8-412a-8eaf-817ff9d665d2 · inbound

Adversarial Agent Behavior Learning in Autonomous Driving Using Deep Reinforcement Learning cites this paper.

Adversarial Agent Behavior Learning in Autonomous Driving Using Deep Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 13

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no resolver link, observed 2026-08-05T18:06:20.546964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:06:20.546964Z digest=sha256:5b24af4bbde8b10d78e73b403a5a982e4be65d0c14d8b475486cfa3a742b2db8

Observation 8c3ad9dd-ce05-417b-aca8-ab1590a464e8 · inbound

Coupling Smoothed Particle Hydrodynamics with Multi-Agent Deep Reinforcement Learning for Cooperative Control of Point Absorbers cites this paper.

Coupling Smoothed Particle Hydrodynamics with Multi-Agent Deep Reinforcement Learning for Cooperative Control of Point Absorbers Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 33

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no resolver link, observed 2026-08-03T11:28:08.546939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T11:28:08.546939Z digest=sha256:8d3bbe31d23d12e7bd1393ae58232480651efef10feaea600ce9d92fa082959a

Observation 8b4c9fb9-86a5-4708-8b81-74db61bec164 · inbound

Multi-agent DRL-based Lane Change Decision Model for Cooperative Platooning in Mixed Traffic cites this paper.

Multi-agent DRL-based Lane Change Decision Model for Cooperative Platooning in Mixed Traffic Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 2020

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no resolver link, observed 2026-08-03T10:04:45.505225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:04:45.505225Z digest=sha256:f7212c5bbe665b577d47ded275c09dc118dda3654fd19f92fc0fc645000d1f1d

Observation a9455798-9ce8-48f2-be50-2b818e0d3776 · inbound

Scalable Neighborhood-Based Multi-Agent Actor-Critic cites this paper.

Scalable Neighborhood-Based Multi-Agent Actor-Critic Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:23:38.015474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T05:19:42.391924Z digest=sha256:34459d8a8b9a574df7b0ef0fc907cf1c7ee7b852497128d6574ad8905fd2f043

Observation c209a0a2-5274-47a7-8fab-5d7a972ab174 · inbound

A Distributionally Robust Reinforcement Learning Framework for Constrained Urban EV Dispatch cites this paper.

A Distributionally Robust Reinforcement Learning Framework for Constrained Urban EV Dispatch Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 31

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verified exact
arxiv_id, observed 2026-05-09T01:59:36.103478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-07T16:14:02.445730Z digest=sha256:902c2888e2e60da876077e8d3bafd5f8a01b3aac27844dc9bc67ed8117356f4f

Observation 145cafc4-4571-4afa-bf09-e452f6b77f16 · inbound

Coordination Architecture Shapes Continuous Demand Response Outcomes in Building Districts cites this paper.

Coordination Architecture Shapes Continuous Demand Response Outcomes in Building Districts Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-09T19:50:54.932340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-09T18:28:25.485844Z digest=sha256:a1d7fe0dee7c076cb94d219f8e31c04b2de3366a3218182d156b0b7cbdf80bdf

Observation a3b5056b-ce0a-48e6-987b-85017737ee79 · inbound

Topology-Driven Anti-Entanglement Control for Soft Robots cites this paper.

Topology-Driven Anti-Entanglement Control for Soft Robots Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 15

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metadata mismatch
arxiv_id, observed 2026-05-11T15:41:27.845264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-09T19:28:39.040470Z digest=sha256:440e6b111eb4ed8e61685b228fb23d06338ecac48ea0e52fc3deb7fb3ad1b1fe

Observation 3fd352ef-0905-4f57-94ba-d7b12479f5d9 · inbound

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models cites this paper.

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 83

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verified exact
arxiv_id, observed 2026-05-12T01:11:13.391298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T01:10:24.579325Z digest=sha256:4e7ff39093013bba833aac585e7316323e2cfd1dfecb5da4c7ad5c011589dc74

Observation 0d3eaab0-cbe4-49db-a7a0-17143fcd9a9f · inbound

Quantum Advantage in Multi Agent Reinforcement Learning cites this paper.

Quantum Advantage in Multi Agent Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 4

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verified exact
arxiv_id, observed 2026-05-15T01:48:28.088425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T01:47:50.831972Z digest=sha256:cfb8a59ea850d498a5885706ed912fdbba8f1ecc55860895882e9c815e41dcda

Observation f90aed9e-7fae-45e2-bb1e-7025a7b2ece0 · inbound

Decoupled Delay Compensation: Enhancing Pre-trained MARL Policies via Learned Dynamics Filtering cites this paper.

Decoupled Delay Compensation: Enhancing Pre-trained MARL Policies via Learned Dynamics Filtering Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 26

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verified exact
arxiv_id, observed 2026-06-29T19:03:51.155793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T19:02:39.358444Z digest=sha256:ae7c0b1d3527c3a05511cee7ebd8c47f5cad3a6b19ee7c2422f0f3dc1df2177a

Observation 03143dbd-beec-43c1-8bf2-49528f85534b · inbound

Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environment cites this paper.

Fog of Love: Engineering Virtuous Agent Behavior with Affinity-based Reinforcement Learning in a Game Environment Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 46

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metadata mismatch
arxiv_id, observed 2026-07-02T08:16:48.147611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T06:12:02.256044Z digest=sha256:9b3e02d6a1bf6b87a198774371dcb339007bb33be01df37aeffcb48f30107445

Observation ba409c5b-2330-44f0-abfa-e58374966b27 · inbound

Integrated Altruistic and Fairness Preference Induces Advanced Mutual Cooperation in Sequential Social Dilemmas cites this paper.

Integrated Altruistic and Fairness Preference Induces Advanced Mutual Cooperation in Sequential Social Dilemmas Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 23

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no resolver link, observed 2026-07-11T14:47:06.125148Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T14:47:06.125148Z digest=sha256:11716d1098089d8b7a9408f0c269b34e59ebeb1a0bbf22cec65a10d002d10e4e

Observation b9274cfc-b6e0-4142-b14a-a8af1d89ebc4 · inbound

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning cites this paper.

Conflict Resolution under Degraded Surveillance in Air Corridors Using Multi-Agent Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 30

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no resolver link, observed 2026-08-02T06:47:35.162165Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T06:47:35.162165Z digest=sha256:3c8e4630a5474eb41e3c2d0cd6fe35b73a1cc1e204298c981a99beb925764ead

Observation 7b356555-7ead-4acf-ba0d-1b8934c27e8a · inbound

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details cites this paper.

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 136

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no resolver link, observed 2026-08-05T15:25:39.914940Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T15:25:39.914940Z digest=sha256:235a8982853b50953ec25a7ecd937baea9f40a981df64fd19f4bf0dd09517eb8

Observation 0910d91b-5b46-4b2a-9236-01e8c16802e6 · inbound

Calibrating Artificial Guilt: Neurally Grounded Reward Shaping for Prosocial Multi-Agent Reinforcement Learning cites this paper.

Calibrating Artificial Guilt: Neurally Grounded Reward Shaping for Prosocial Multi-Agent Reinforcement Learning Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments

Reference 30

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no resolver link, observed 2026-08-06T19:33:39.032751Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:33:39.032751Z digest=sha256:43469f5e1dcdeb6ef01ee82af39066e2995dc5ad13056cdaffd08c9100f7893c