Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:12:00.525994Z
Paper Citation Record · LEDGER
Novel Multi-Agent Action Masked Deep Reinforcement Learning for General Industrial Assembly Lines Balancing Problems
As of 9 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2507.16635.
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 2026-08-09T06:31:02.800959+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
46 of 46 outbound references displayed
- verified exact0
- verified fuzzy41
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.