Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems | Paper Citation Record

Observation a60dc660-fc2e-4176-9b10-6b791ad00e46 · outbound

This paper cites Literature review of assembly line balancing problems,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Literature review of assembly line balancing problems,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.834292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7c5f4fd4-ab06-4c8f-8282-8f8e83a0ec80 · outbound

This paper cites Literature review of industry 4.0 and related technologies,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Literature review of industry 4.0 and related technologies,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.814801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5ceb875d-bb25-42dd-8fd7-4e3e0ed59d8c · outbound

This paper cites The assembly-line balancing problem,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems The assembly-line balancing problem,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.793525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6450402d-6be8-47e8-ade8-b71ac2084623 · outbound

This paper cites A survey on multi-agent reinforcement learning and its application,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A survey on multi-agent reinforcement learning and its application,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.771647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7cd47ef0-d8b0-4318-8f83-e8c09607497d · outbound

This paper cites Novel hybrid integrated pix2pix and wgan model with gradient penalty for binary images denoising,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Novel hybrid integrated pix2pix and wgan model with gradient penalty for binary images denoising,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.722871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cd5765df-c894-4c13-8aec-bc112d3f9100 · outbound

This paper cites Segnet: A segmented deep learning based convolutional neural network approach for drones wildfire detection,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Segnet: A segmented deep learning based convolutional neural network approach for drones wildfire detection,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.678676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8cbc3877-497a-4844-b208-7349a355b621 · outbound

This paper cites Sampled-data control through model-free reinforcement learning with effective experience replay,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Sampled-data control through model-free reinforcement learning with effective experience replay,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.652825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3001f66d-5696-4337-b131-5f21906fc4a0 · outbound

This paper cites Comprehensive and comparative analysis between transfer learning and custom built vgg and cnn-svm models for wildfire detection,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Comprehensive and comparative analysis between transfer learning and custom built vgg and cnn-svm models for wildfire detection,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.618973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0145927f-b1a3-42c8-aa3a-364463537712 · outbound

This paper cites Reinforcement learning with soft temporal logic constraints using limit-deterministic generalized büchi automaton,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Reinforcement learning with soft temporal logic constraints using limit-deterministic generalized büchi automaton,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.562584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5f7eb199-06b6-4494-91dd-f04938df8e5a · outbound

This paper cites A new optimal adaptive backstepping control ap- proach for nonlinear systems under deception attacks via reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A new optimal adaptive backstepping control ap- proach for nonlinear systems under deception attacks via reinforcement learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.535525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 49a3df57-2cf2-4750-92e3-299a8af4a4ce · outbound

This paper cites A comprehensive survey of robust deep learning in computer vision,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A comprehensive survey of robust deep learning in computer vision,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.471261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd532d48-f108-421f-8d62-27fcf06da4d8 · outbound

This paper cites A taxonomy of line balancing problems and their solution approaches,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A taxonomy of line balancing problems and their solution approaches,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.422961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 27c6577e-c23f-4dd1-968b-a73f81aad4d6 · outbound

This paper cites Balancing of parallel u-shaped assembly lines,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Balancing of parallel u-shaped assembly lines,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.394419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6e3c7bc3-5e51-4290-8cc7-c20dfa022cb4 · outbound

This paper cites Scheduling and operator control in reconfigurable assembly systems,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Scheduling and operator control in reconfigurable assembly systems,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.358908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c8cf666a-5b80-4437-b536-63670d329efa · outbound

This paper cites Rolling horizon production scheduling of multi-model pcbs for several assembly lines,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Rolling horizon production scheduling of multi-model pcbs for several assembly lines,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.315604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation efe84347-acc5-434b-8f1f-4ae8800d4ed2 · outbound

This paper cites A genetic simulated annealing algorithm for parallel partial disassembly line balancing problem,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A genetic simulated annealing algorithm for parallel partial disassembly line balancing problem,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.270385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 737a3671-3fe2-4bac-887d-309507354c15 · outbound

This paper cites Mathematical model and bee algorithms for mixed-model assembly line balancing problem with physical human–robot collaboration,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Mathematical model and bee algorithms for mixed-model assembly line balancing problem with physical human–robot collaboration,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.218494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 91bbe40b-d096-4324-a021-2741f30a9048 · outbound

This paper cites Designing assembly lines with humans and collaborative robots: A genetic approach,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Designing assembly lines with humans and collaborative robots: A genetic approach,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.189214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 60d7c493-8325-47fc-acf4-1f0e7149b83d · outbound

This paper cites A novel bi-level multi-objective genetic algorithm for integrated assembly line balancing and part feeding problem,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A novel bi-level multi-objective genetic algorithm for integrated assembly line balancing and part feeding problem,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.151947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5b43e470-ecd6-4345-9b46-631eba131813 · outbound

This paper cites Robust production planning and capacity control for flexible assembly lines,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Robust production planning and capacity control for flexible assembly lines,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.113929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8aec47df-52d2-4280-89ca-7fc97261786b · outbound

This paper cites An integrated framework for design, management and operation of reconfigurable assembly systems,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems An integrated framework for design, management and operation of reconfigurable assembly systems,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.076196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 31092369-80ae-42a5-b18b-f4ddac75e0ca · outbound

This paper cites Machine learning applications in production lines: A systematic literature review,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Machine learning applications in production lines: A systematic literature review,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:01.020198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 51b7d335-8d62-480a-81b3-c17a6a787dd3 · outbound

This paper cites Two-stage teaching-learning-based optimization method for flexible job-shop scheduling under machine breakdown,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Two-stage teaching-learning-based optimization method for flexible job-shop scheduling under machine breakdown,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.977580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 13268e73-720c-4b9d-baa4-a79de589f1a9 · outbound

This paper cites Deep reinforcement learning-based dynamic scheduling in smart manufacturing,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Deep reinforcement learning-based dynamic scheduling in smart manufacturing,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.947179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 415943ab-fd76-4a25-9bea-fea26aa888e7 · outbound

This paper cites Dynamic job-shop scheduling in smart manufacturing using deep reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Dynamic job-shop scheduling in smart manufacturing using deep reinforcement learning,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.919577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4a6fd7c3-4d58-4f47-97f8-e447a9871aee · outbound

This paper cites Proximal Policy Optimization Algorithms.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Proximal Policy Optimization Algorithms

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T15:12:00.425419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c02c3cf4-bfb9-43fd-a673-43ec1af8ae97 · outbound

This paper cites Human-level control through deep reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Human-level control through deep reinforcement learning,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T15:12:00.430518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8650ca99-472c-48b0-9633-c708a3cb9328 · outbound

This paper cites Safe reinforcement learning via shielding,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Safe reinforcement learning via shielding,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.865157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 07e50d5f-b39a-42f3-8389-29f39ca7fc18 · outbound

This paper cites A Closer Look at Invalid Action Masking in Policy Gradient Algorithms.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A Closer Look at Invalid Action Masking in Policy Gradient Algorithms

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T15:12:00.444992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99ee3005-d64b-41c5-aeff-b08f6c6d2e1c · outbound

This paper cites Safe multi-agent reinforcement learning via shielding,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Safe multi-agent reinforcement learning via shielding,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.848229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ef9429df-c22d-48ae-b9f8-46a3c8941e92 · outbound

This paper cites Distributed actor–critic algo- rithms for multiagent reinforcement learning over directed graphs,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Distributed actor–critic algo- rithms for multiagent reinforcement learning over directed graphs,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.832191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2e5a9ece-b5b5-419a-9494-65077c81835a · outbound

This paper cites Multi-agent reinforce- ment learning: An overview,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Multi-agent reinforce- ment learning: An overview,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.816870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ea6b0d92-d64e-4d9d-abbe-45e9c23e88d7 · outbound

This paper cites A review of cooperative multi-agent deep reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A review of cooperative multi-agent deep reinforcement learning,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.802093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2e105735-705f-4035-bafb-fc4292e546d5 · outbound

This paper cites Cooperative multi-agent control using deep reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Cooperative multi-agent control using deep reinforcement learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.786021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cde371c8-0c50-4b0c-a7fd-ebaf0c36ae12 · outbound

This paper cites Weighted qmix: Expanding monotonic value function factorisation for deep multi-agent reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Weighted qmix: Expanding monotonic value function factorisation for deep multi-agent reinforcement learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.771509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8e88f345-957d-4bea-ad49-440c17707af4 · outbound

This paper cites QPLEX: Duplex Dueling Multi-Agent Q-Learning.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems QPLEX: Duplex Dueling Multi-Agent Q-Learning

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T15:12:00.477165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40abdfad-a171-4ed1-bdfa-b78c06dea085 · outbound

This paper cites Revisiting some common practices in cooperative multi-agent reinforcement learning,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Revisiting some common practices in cooperative multi-agent reinforcement learning,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.756248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ae06f9fb-2bae-4532-abbd-c3ccf573b6c9 · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems The surprising effectiveness of ppo in cooperative multi-agent games,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.741839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 107b7ddd-ddeb-4d7f-81a4-2b45d28d825c · outbound

This paper cites Facmac: Factored multi-agent centralised policy gradients,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Facmac: Factored multi-agent centralised policy gradients,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.726497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 312eb005-aa6e-4cdc-8c22-4b4e242d4930 · outbound

This paper cites Deep reinforcement learning for optimal planning of assembly line maintenance,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Deep reinforcement learning for optimal planning of assembly line maintenance,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.885831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7bd0d137-a521-4d20-8033-dbf221bd300a · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Playing Atari with Deep Reinforcement Learning

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T15:12:00.500251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef2f2021-8482-41c9-8472-f8c6e6f7e69b · outbound

This paper cites Action masked deep reinforcement learning for controlling industrial assembly lines,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Action masked deep reinforcement learning for controlling industrial assembly lines,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.709434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0e654059-cc0f-4f85-8945-0e3909e7b02a · outbound

This paper cites A collaborative multi-agent deep reinforcement learning-based wireless power allocation with centralized training and decentralized execution,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems A collaborative multi-agent deep reinforcement learning-based wireless power allocation with centralized training and decentralized execution,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.693604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 57061b5a-de19-4030-b04d-1dcb56d31786 · outbound

This paper cites Deep reinforcement learning for multi-agent power control in heterogeneous networks,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Deep reinforcement learning for multi-agent power control in heterogeneous networks,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.677393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fee378ed-6fbc-4909-bcda-dba3b221f6b6 · outbound

This paper cites Age of information minimization using multi-agent uavs based on ai-enhanced mean field resource allocation,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Age of information minimization using multi-agent uavs based on ai-enhanced mean field resource allocation,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.660710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5cdcf6fe-f7dd-4115-a09f-0c233b48906e · outbound

This paper cites Deep reinforcement learning for sim-to-real policy transfer of vtol-uavs offshore docking operations,.

Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems Deep reinforcement learning for sim-to-real policy transfer of vtol-uavs offshore docking operations,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:12:00.645121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers