Paper Citation Record · LEDGER

Multi-agent Reinforcement Learning: A Comprehensive Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2312.10256.

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

pith.paper-citation-record.v1
2312.10256 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:19:43.882854Z

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

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

9
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 267555ed-9429-4640-b87a-43048ef1a28d · inbound

LLM-Powered Decentralized Generative Agents with Adaptive Hierarchical Knowledge Graph for Cooperative Planning cites this paper.

LLM-Powered Decentralized Generative Agents with Adaptive Hierarchical Knowledge Graph for Cooperative Planning Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-08T19:19:43.882854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec0765bb-437e-40c6-8037-1679f70e33d7 · inbound

Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G cites this paper.

Multi-Agent Reinforcement Learning in Wireless Distributed Networks for 6G Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 145

Resolution: unresolved; no resolver link, observed 2026-08-08T17:54:46.513662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af5d2004-caaf-47b6-ac61-7b0028f94f0a · 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 Reinforcement Learning: A Comprehensive Survey

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:10:40.061190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 876472e3-9c87-4479-b2e4-b8f56a2be4f3 · inbound

AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need cites this paper.

AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:59:47.982531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 862c2bdf-51a2-4d24-b699-85185337629b · inbound

Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning cites this paper.

Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T10:40:38.764919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a445999-f65f-4c74-8227-913d327376e2 · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-18T19:21:48.282484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 72b51e1f-523b-4a3e-bccf-bcabd1e154c8 · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 218

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:05:31.635283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f96b8d00-0f75-4660-8149-f5f2cafa157f · inbound

Subjective-Graph LLM Agents for Simulating Uncertainty in Classroom Social Perception cites this paper.

Subjective-Graph LLM Agents for Simulating Uncertainty in Classroom Social Perception Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-13T21:18:07.586683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23ecf2ec-e549-4d79-9992-291af1b23257 · inbound

Building Better Environments for Autonomous Cyber Defence cites this paper.

Building Better Environments for Autonomous Cyber Defence Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:11:03.788009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3ffb94aa-6d67-45db-93d7-739f5032977d · inbound

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures cites this paper.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.089215Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation acf5e0b6-ec12-4f3f-a450-410f2e91bf35 · inbound

MAGIC: Multi-Step Advantage-Gated Causal Influence for Multi-agent Reinforcement Learning cites this paper.

MAGIC: Multi-Step Advantage-Gated Causal Influence for Multi-agent Reinforcement Learning Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T16:31:09.293003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0cf26807-cba0-4c17-b1b4-e8efe1a9572c · inbound

TRACER: Turn-level Regret Matching with Inner Reinforcement Credit for Cooperative Multi-LLM Reasoning cites this paper.

TRACER: Turn-level Regret Matching with Inner Reinforcement Credit for Cooperative Multi-LLM Reasoning Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:23:23.810958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2546e38-9ed0-47bc-92c9-3cc7c68b2b97 · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T20:56:13.360634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2fb30b31-c1dd-4828-89ec-d2cfaff0698f · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:09:40.724416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 255c085f-74ad-4dd3-ab3a-4445d8a1d335 · inbound

Asymmetric physics enables efficient learning in quadrupedal robot swarms cites this paper.

Asymmetric physics enables efficient learning in quadrupedal robot swarms Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:49:45.775933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e7f564a2-9086-455b-9a5c-5ff10f6b4663 · inbound

TrustChain-Review: A Risk-Adaptive Blockchain and Game-Theoretic Framework for Trustworthy AI-Assisted Code Review cites this paper.

TrustChain-Review: A Risk-Adaptive Blockchain and Game-Theoretic Framework for Trustworthy AI-Assisted Code Review Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T09:47:57.722607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.