Paper Citation Record · LEDGER

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:1803.11485.

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

pith.paper-citation-record.v1
1803.11485 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 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 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:00:56.959209Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T01:47:31.633962Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 54ee2cec-3397-4aeb-9344-32ad565ab6b1 · inbound

Growing Action Spaces cites this paper.

Growing Action Spaces QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-25T13:25:52.390433Z

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 dfd17dd2-ed62-4e2a-92ca-30e016d7eab3 · inbound

Multiple Landmark Detection using Multi-Agent Reinforcement Learning cites this paper.

Multiple Landmark Detection using Multi-Agent Reinforcement Learning QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 18

Resolution: metadata mismatch; local_arxiv, observed 2026-05-25T13:10:50.868328Z

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 38e9cab4-1a82-4335-aed5-c20bcfdb4bf7 · inbound

M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference cites this paper.

M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T23:00:56.959209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06ab5a4c-c03b-4b17-bef6-9745459ae6a3 · inbound

TACTIC: Task-Agnostic Contrastive pre-Training for Inter-Agent Communication cites this paper.

TACTIC: Task-Agnostic Contrastive pre-Training for Inter-Agent Communication QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T22:17:51.443174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7409bc06-3ab6-4ede-82b8-7961462e6e08 · inbound

Revisiting Communication Efficiency in Multi-Agent Reinforcement Learning from the Dimensional Analysis Perspective cites this paper.

Revisiting Communication Efficiency in Multi-Agent Reinforcement Learning from the Dimensional Analysis Perspective QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T22:06:27.906102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b84138cd-d151-40ab-a4db-8bef2a38c59b · inbound

CSAOT: Cooperative Multi-Agent System for Active Object Tracking cites this paper.

CSAOT: Cooperative Multi-Agent System for Active Object Tracking QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T15:55:14.114029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ee11d50-1715-46c3-9323-b425b5b391db · inbound

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning cites this paper.

Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 105

Resolution: unresolved; no resolver link, observed 2026-08-09T17:58:35.763989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c269d0a-b0bd-4b2c-aa44-996adb9d5424 · inbound

MAGNNET: Multi-Agent Graph Neural Network-based Efficient Task Allocation for Autonomous Vehicles with Deep Reinforcement Learning cites this paper.

MAGNNET: Multi-Agent Graph Neural Network-based Efficient Task Allocation for Autonomous Vehicles with Deep Reinforcement Learning QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T12:38:20.804719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 098c8271-be96-413c-8423-471f8dbf8779 · 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 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T18:50:49.855234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66162488-6c90-4c99-a12c-707e2585dbe3 · inbound

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

Multi-Agent Reinforcement Learning in Cybersecurity: From Fundamentals to Applications QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T14:10:42.528804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbeecba4-df41-4b81-83a4-5ee1fa5b4c80 · inbound

Zero-Incentive Dynamics: a look at reward sparsity through the lens of unrewarded subgoals cites this paper.

Zero-Incentive Dynamics: a look at reward sparsity through the lens of unrewarded subgoals QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T20:59:15.058602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b32f4b0c-3907-41a0-a7e1-c7ce722d5905 · inbound

Multi-Agent Reinforcement Learning for Dynamic Pricing in Supply Chains: Benchmarking Strategic Agent Behaviours under Realistically Simulated Market Conditions cites this paper.

Multi-Agent Reinforcement Learning for Dynamic Pricing in Supply Chains: Benchmarking Strategic Agent Behaviours under Realistically Simulated Market Conditions QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:14.571680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b66142a-d4d1-4d0b-b2ef-9e2057a5e2fa · inbound

Application of LLMs to Multi-Robot Path Planning and Task Allocation cites this paper.

Application of LLMs to Multi-Robot Path Planning and Task Allocation QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:48:17.851187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da89a05e-8d52-4173-86df-687d8d2efb19 · 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 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T17:29:19.305829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e68724c-db5e-45aa-9111-e60f4057b37a · inbound

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration cites this paper.

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T17:49:14.861524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4c98b64-bd6f-47bc-a706-7e3f382a7291 · inbound

AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning cites this paper.

AdaFair-MARL: Enforcing Adaptive Fairness Constraints in Multi-Agent Reinforcement Learning QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-05-17T20:20:11.869823Z

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 12a950e0-e4a3-4dae-8a33-bf07e2f8c1ac · inbound

DelAC: A Multi-agent Reinforcement Learning of Team-Symmetric Stochastic Games cites this paper.

DelAC: A Multi-agent Reinforcement Learning of Team-Symmetric Stochastic Games QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-14T21:32:59.329298Z

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 dbefc2e8-5156-4a0e-917d-cf0767f8b822 · 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 QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-06-29T19:03:51.193730Z

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 cfb1c807-3097-4e16-9afa-0ea1a8a831bb · inbound

MASK: Multi-Agent Semantic K-Scheduling for Risk-Sensitive 6G Robotics cites this paper.

MASK: Multi-Agent Semantic K-Scheduling for Risk-Sensitive 6G Robotics QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-03T01:47:31.635928Z

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.