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Paper Citation Record · LEDGER

LineFlow: A Framework to Learn Active Control of Production Lines

As of 20 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2505.06744.

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

pith.paper-citation-record.v1
2505.06744 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:39:59.399768Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

57 of 57 outbound references displayed

  • verified exact13
  • verified fuzzy16
  • unresolved26
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 50ba5009-d3a9-4f63-a6c0-8acbf8489128 · outbound

This paper cites write newline.

LineFlow: A Framework to Learn Active Control of Production Lines write newline

Reference 1

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no resolver link, observed 2026-08-15T22:39:59.149489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.149489Z digest=sha256:590110945de31848ad697154248f48826128921ad710c4db1246224bd9c1ec96

Observation bceb6105-303c-4ff8-8a20-7f8c9fa1ce1b · outbound

This paper cites an unresolved cited work.

LineFlow: A Framework to Learn Active Control of Production Lines Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-15T22:39:59.155997Z digest=sha256:f882685555e2a2f9fc424bb3dd515cc338669891c507762e3a70733a9ca9f1a9

Observation 5854cff2-8792-452e-be4c-2ae3c76dd649 · outbound

This paper cites Gekko optimization suite.

LineFlow: A Framework to Learn Active Control of Production Lines Gekko optimization suite

Reference 3

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no resolver link, observed 2026-08-15T22:39:59.161399Z

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source=arxiv_source observed=2026-08-15T22:39:59.161399Z digest=sha256:f59dfea0fb1eed6348305c34d063f6c2f2b02629388ac785879d60db44ecfb0e

Observation c250bd86-b78e-47ea-8429-bf2235df2c39 · outbound

This paper cites Performance analysis of production lines: Discrete and continuous flow models.

LineFlow: A Framework to Learn Active Control of Production Lines Performance analysis of production lines: Discrete and continuous flow models

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.849191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.166055Z digest=sha256:9d0300c265efb2ff5cc6d78e6f214b16e3c6335eb2b4df7b233c7b642215d64f

Observation 04688864-bc5d-41b3-8224-d2b051d7c093 · outbound

This paper cites Modeling and control of dispensing processes for surface mount technology.

LineFlow: A Framework to Learn Active Control of Production Lines Modeling and control of dispensing processes for surface mount technology

Reference 5

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metadata mismatch
raw_fallback, observed 2026-08-15T22:40:00.501864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.170232Z digest=sha256:767144008be16651826520ff66b4e5fb97cf0e3f00bfbcbb60cef0b236d5df5e

Observation 59f2bcb1-4d23-43e6-8e68-a487073ac039 · outbound

This paper cites Y., Malyutin, S., and Soukhal, A.

LineFlow: A Framework to Learn Active Control of Production Lines Y., Malyutin, S., and Soukhal, A

Reference 6

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verified exact
doi, observed 2026-08-15T22:39:59.644752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.174329Z digest=sha256:cc17c4076dde273d6d42879f822409a06f8f002ae63c87c334c03baf59761282

Observation cb3945bb-0e1f-41a5-887a-e3ea9be0d1e1 · outbound

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

LineFlow: A Framework to Learn Active Control of Production Lines Deep reinforcement learning for optimal planning of assembly line maintenance

Reference 7

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.631147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.178578Z digest=sha256:804317058cb54ee7b3bcfda143cf6d6a8b8b0ec485c29d67183593e5523f7406

Observation 79b9d5cd-7505-467e-9ce1-cc505d04c579 · outbound

This paper cites N., Cortez, P., Carvalho, M.

LineFlow: A Framework to Learn Active Control of Production Lines N., Cortez, P., Carvalho, M

Reference 8

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no resolver link, observed 2026-08-15T22:39:59.183777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.183777Z digest=sha256:0c9c2fbf0096c101f386b83505c9c2292c7bbabb13c62febf08a0e86791b02c0

Observation ac3160a9-f917-4f02-9578-e0acfed2fea3 · outbound

This paper cites A reinforcement learning decision model for online process parameters optimization from offline data in injection molding.

LineFlow: A Framework to Learn Active Control of Production Lines A reinforcement learning decision model for online process parameters optimization from offline data in injection molding

Reference 9

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no resolver link, observed 2026-08-15T22:39:59.188789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.188789Z digest=sha256:f50aedf0b8d1c944bbfd059c932116f1186dae69b70291850f87a30ee554db62

Observation ae6f6408-e295-405f-9da1-f9dee8e1e1ef · outbound

This paper cites R., Millman, K.

LineFlow: A Framework to Learn Active Control of Production Lines R., Millman, K

Reference 10

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no resolver link, observed 2026-08-15T22:39:59.193364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.193364Z digest=sha256:6dce302c6676cbf0529f4434f709e82b0802373718e341b9bf9224a3ecf7bc78

Observation 5ee6a24a-a1b6-44e6-b977-d441ac58241a · outbound

This paper cites Memory-based control with recurrent neural networks.

LineFlow: A Framework to Learn Active Control of Production Lines Memory-based control with recurrent neural networks

Reference 11

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no resolver link, observed 2026-08-15T22:39:59.198374Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.198374Z digest=sha256:1321bce06ef0dcb0e1ca11c0ecca581864f15b3c7eccdafcb247030884175287

Observation 91748e3b-809d-4667-a924-202ab64a0dfb · outbound

This paper cites Y., and Jiang, J.

LineFlow: A Framework to Learn Active Control of Production Lines Y., and Jiang, J

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.834574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.203111Z digest=sha256:6b015cf07131a63e0cbc6d929c000beead5d0a3bda62e2b0253398e82dd00f28

Observation 9e3cc7cd-3f3d-4b32-b087-1f8279fc5206 · outbound

This paper cites An intelligent weld control strategy based on reinforcement learning approach.

LineFlow: A Framework to Learn Active Control of Production Lines An intelligent weld control strategy based on reinforcement learning approach

Reference 13

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.608458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.207287Z digest=sha256:15df27da8a044f2478710b4d2dfa37e2066c73a4b6da95ad79661c0988c0a793

Observation 329c674a-f5af-4c87-9dd3-66a4a6bec620 · outbound

This paper cites M., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Ž \'i dek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S.

LineFlow: A Framework to Learn Active Control of Production Lines M., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Ž \'i dek, A., Potapenko, A., Bridgland, A., Meyer, C., Kohl, S

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.818605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.212526Z digest=sha256:b7c8a6a1d2ecb004e51672d1f6ff375f19f0c6cab49ae032e3cc3c8fa2816cef

Observation 5a027b3f-1dda-417b-b9c9-32063c4ad054 · outbound

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

LineFlow: A Framework to Learn Active Control of Production Lines Machine learning applications in production lines: A systematic literature review

Reference 15

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.217461Z digest=sha256:867c386067820b519e9daeacaf07fd13a57e8323631c14dca922ca05c071e612

Observation 69a5083d-f6bc-43b8-9982-df765c4ab58f · outbound

This paper cites an unresolved cited work.

LineFlow: A Framework to Learn Active Control of Production Lines Unresolved cited work

Reference 16

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verified exact
doi, observed 2026-08-15T22:39:59.594845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.221688Z digest=sha256:75207e905b31066f92b9e2d7d3e086de64f754e252ed515448627c2959a6e761

Observation bba75d2f-0b77-4217-862e-042664a6f2f6 · outbound

This paper cites Designing an adaptive production control system using reinforcement learning.

LineFlow: A Framework to Learn Active Control of Production Lines Designing an adaptive production control system using reinforcement learning

Reference 17

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.581023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.226817Z digest=sha256:038c749765928ce54bdd8a81d672aee61181e22b349e36f576a89f8bb704a484

Observation aa38bf9a-b8ca-44ce-85e2-7d128d153008 · outbound

This paper cites Data-driven dynamic bottleneck detection in complex manufacturing systems.

LineFlow: A Framework to Learn Active Control of Production Lines Data-driven dynamic bottleneck detection in complex manufacturing systems

Reference 18

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.565976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.231051Z digest=sha256:32cb39900ed1b0b9c5418c651fb2ecadb8a1b015aa2d0894ec4557035ae61ab7

Observation daaf5337-de38-4551-93d5-33f9efd66be6 · outbound

This paper cites Real time production improvement through bottleneck control.

LineFlow: A Framework to Learn Active Control of Production Lines Real time production improvement through bottleneck control

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.804620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.235265Z digest=sha256:862001dd9f4d81ac759cc915478c8f279669d005f28e2b2909a9cce7ce2bfec5

Observation 300996e9-3e49-4352-b109-8cbd7c65367b · outbound

This paper cites T., Tan, B.

LineFlow: A Framework to Learn Active Control of Production Lines T., Tan, B

Reference 20

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verified exact
doi, observed 2026-08-15T22:39:59.551601Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.239601Z digest=sha256:9edea38706204ce47f1473f38f2b52fb6f8c455cafd2a7272007dbd61ba764c1

Observation 59dea9fb-2bca-4f03-86e7-71e5d9d69f75 · outbound

This paper cites C., Schäfer, L., Matta, A., and Lanza, G.

LineFlow: A Framework to Learn Active Control of Production Lines C., Schäfer, L., Matta, A., and Lanza, G

Reference 21

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verified exact
doi, observed 2026-08-15T22:39:59.535798Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.243966Z digest=sha256:c833c4dddaab6a9da5da038027d765602b5dc1ffd27bb57e60317a3509cb1762

Observation 72d9093c-e4b7-4c5f-95c9-04522e82729d · outbound

This paper cites C., Matta, A., and Lanza, G.

LineFlow: A Framework to Learn Active Control of Production Lines C., Matta, A., and Lanza, G

Reference 22

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doi, observed 2026-08-15T22:39:59.522117Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.249264Z digest=sha256:c46a8e442202cd7873f3b2b755ac2f3c32959e8bec97f2a931800c6bec9ba7b5

Observation b7f173c9-4107-4da8-8310-870230cfd795 · outbound

This paper cites The impact of industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives.

LineFlow: A Framework to Learn Active Control of Production Lines The impact of industry 4.0 on bottleneck analysis in production and manufacturing: Current trends and future perspectives

Reference 23

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.254371Z digest=sha256:b95769c8ba4a1241b41d9b28c70c00ac9f4f9c9d1d6f3bbedc0822edfed413df

Observation ea579b42-9c2f-406d-ab4c-601848b4dbe5 · outbound

This paper cites an unresolved cited work.

LineFlow: A Framework to Learn Active Control of Production Lines Unresolved cited work

Reference 24

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no resolver link, observed 2026-08-15T22:39:59.258716Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.258716Z digest=sha256:3e55f7334d9c3028b1c312d058af4283c52228e3a2e081b0105e3e646524d29c

Observation 2279ebbc-cedc-48be-8d18-1fb1ce770067 · outbound

This paper cites P., Mirza, M., Graves, A., Lillicrap, T., Harley, T., Silver, D., and Kavukcuoglu, K.

LineFlow: A Framework to Learn Active Control of Production Lines P., Mirza, M., Graves, A., Lillicrap, T., Harley, T., Silver, D., and Kavukcuoglu, K

Reference 25

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no resolver link, observed 2026-08-15T22:39:59.262953Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.262953Z digest=sha256:8c1e61b5b53be91d9fc09ffd664f955849b7096098859a8a736da5f85163b35c

Observation d7f92f87-9c04-49f9-b92f-ab309c6832e3 · outbound

This paper cites Introduction to TPM: Total Productive Maintenance.

LineFlow: A Framework to Learn Active Control of Production Lines Introduction to TPM: Total Productive Maintenance

Reference 26

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raw_fallback, observed 2026-08-15T22:40:00.781504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.267293Z digest=sha256:597761b205c2f1274cf7b540e71106cff61ba7e04b71b690d4ad27ccf9834ba0

Observation d958b0c1-3d29-4150-88a0-9b23f6777752 · outbound

This paper cites E., and Stone, P.

LineFlow: A Framework to Learn Active Control of Production Lines E., and Stone, P

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.766019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.271609Z digest=sha256:59694c6ac8b2b4adc85de7ae6afb6c983ababd9fb6e08364a2699a0262966b68

Observation 051b0705-cb04-461f-8501-fd4012f46935 · outbound

This paper cites A review on reinforcement learning: Introduction and applications in industrial process control.

LineFlow: A Framework to Learn Active Control of Production Lines A review on reinforcement learning: Introduction and applications in industrial process control

Reference 28

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.276001Z digest=sha256:01f5b5a819a464cabbb3459e0aa97ac91d661663989ae059d5495036be384620

Observation 312fb8cc-46cb-4f8c-8f4a-b9193c54f029 · outbound

This paper cites C., Kuhnle, A., and Lanza, G.

LineFlow: A Framework to Learn Active Control of Production Lines C., Kuhnle, A., and Lanza, G

Reference 29

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verified exact
doi, observed 2026-08-15T22:39:59.506981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.280319Z digest=sha256:206fd0d780ef1cbd19fb7008665749e4d674c3344657528d98ba65b51b021d61

Observation f8f0378b-3e3c-4e92-98b3-ad5c633382d6 · outbound

This paper cites Irizarry, M., Resto, P., and Mej \' a, H.

LineFlow: A Framework to Learn Active Control of Production Lines Irizarry, M., Resto, P., and Mej \' a, H

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.752314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.284548Z digest=sha256:ef1cfa54ce6a40ea55435d2a2223630632fe7d1eb331e0451332ea0a28eea180

Observation 23f34723-89e1-4ea1-be3d-89a487f61372 · outbound

This paper cites Generalization, Mayhems and Limits in Recurrent Proximal Policy Optimization.

LineFlow: A Framework to Learn Active Control of Production Lines Generalization, Mayhems and Limits in Recurrent Proximal Policy Optimization

Reference 31

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no resolver link, observed 2026-08-15T22:39:59.288557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.288557Z digest=sha256:78841edfa4f3f8e4e3b4b5c6c17261a21fd19b5d9349c9800b85882a72f78bff

Observation 1389f7e9-d515-432d-a38f-dc1cb26750cb · outbound

This paper cites Memory gym: Partially observable challenges to memory-based agents.

LineFlow: A Framework to Learn Active Control of Production Lines Memory gym: Partially observable challenges to memory-based agents

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.738422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.293050Z digest=sha256:70d435c686c987ab14eeb9ebb85e4d26ae4f1e0aa90dbc80794a217c7433da7e

Observation 6c73cd76-db09-4376-be44-1659b0f91926 · outbound

This paper cites M., Ou, W., Yenradee, P., and Huynh, V.-N.

LineFlow: A Framework to Learn Active Control of Production Lines M., Ou, W., Yenradee, P., and Huynh, V.-N

Reference 33

Resolution
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no resolver link, observed 2026-08-15T22:39:59.297366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.297366Z digest=sha256:f2f0e47e9e545b461f26b02037f60a09dffce893b4554bc77af9696e41709786

Observation 8b3f6244-2135-4fd1-8589-915e857cb817 · outbound

This paper cites Stable-baselines3: Reliable reinforcement learning implementations.

LineFlow: A Framework to Learn Active Control of Production Lines Stable-baselines3: Reliable reinforcement learning implementations

Reference 34

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no resolver link, observed 2026-08-15T22:39:59.301361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.301361Z digest=sha256:a33fc87942b4ff6f7b31dfe7e35b9a2dd9b6b1fc5743a6f4690061827da52104

Observation 1631eb60-7f27-44cf-bb30-500527e06749 · outbound

This paper cites Bosch production line performance.

LineFlow: A Framework to Learn Active Control of Production Lines Bosch production line performance

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.715879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.305500Z digest=sha256:e483b3587f0390eb80cd061cf631ad4aee91baf60c5a2dd445e683caaec64754

Observation ed99d3bf-44aa-4a9c-a17e-b97e445630f0 · outbound

This paper cites Shifting bottleneck detection.

LineFlow: A Framework to Learn Active Control of Production Lines Shifting bottleneck detection

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.701945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.309838Z digest=sha256:b80b5c2779b544dd605771e9168fe6e09ba1862fa6a9f6b6ab29488ae739b576

Observation 437a01d4-8585-4b1b-a4d2-8ca26abe9551 · outbound

This paper cites Reliable shop floor bottleneck detection for flow lines through process and inventory observations.

LineFlow: A Framework to Learn Active Control of Production Lines Reliable shop floor bottleneck detection for flow lines through process and inventory observations

Reference 37

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.492576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.313880Z digest=sha256:c90530734a2bdf691b3aa631e5af74ae36204ea0ca698e94f932a376a9346621

Observation eb3bc357-f753-4beb-a063-dc5247f4570a · outbound

This paper cites Bottleneck prediction using the active period method in combination with buffer inventories.

LineFlow: A Framework to Learn Active Control of Production Lines Bottleneck prediction using the active period method in combination with buffer inventories

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.687674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.318002Z digest=sha256:f16cf25b8f7732e0bbcf9c86d67f603f0efd26b2c7aff5daffd0870ae786b4b5

Observation c6f55455-8b5b-48a6-a847-408b9ee0b99c · outbound

This paper cites and Becker, C.

LineFlow: A Framework to Learn Active Control of Production Lines and Becker, C

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.673362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.322130Z digest=sha256:ccc0d7ecb0f4ebbe27258034fecda4bb157b0786f928240baef3a34e09ac521b

Observation 8d9db04b-102d-4cd7-854f-4d05791bb481 · outbound

This paper cites Trust region policy optimization.

LineFlow: A Framework to Learn Active Control of Production Lines Trust region policy optimization

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.326009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.326009Z digest=sha256:c1b5dbf5b9a4e8419ae20f05e373c5f754b84444e8db07399d964ab49ba0d1e0

Observation d8f81b86-b7a8-498e-a9d7-e9c45848db2f · outbound

This paper cites Proximal Policy Optimization Algorithms.

LineFlow: A Framework to Learn Active Control of Production Lines Proximal Policy Optimization Algorithms

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.330079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.330079Z digest=sha256:fb5a9bebbb727a77496fc34147db0ce56fbf40c4c1e8d49b03013d01f0ad0f21

Observation 82cad94f-99ff-4e19-9311-6ea8d3b37511 · outbound

This paper cites skrl: Modular and flexible library for reinforcement learning.

LineFlow: A Framework to Learn Active Control of Production Lines skrl: Modular and flexible library for reinforcement learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.650384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.334146Z digest=sha256:f02113bd423765b168ffbac1972ec1ba13a8a1185cee9146dbe726e0502b4dd9

Observation 6d1654b2-7410-43f1-ae8c-17d6145dadcd · outbound

This paper cites Intelligent scheduling of discrete automated production line via deep reinforcement learning.

LineFlow: A Framework to Learn Active Control of Production Lines Intelligent scheduling of discrete automated production line via deep reinforcement learning

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.338352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.338352Z digest=sha256:c3205a01f77a34d606d06b29e4cce2cd26ca1b8fca2cab4f965d574fc396018e

Observation 7b369288-dd34-4a34-be5e-1f44e517ee57 · outbound

This paper cites Real-time scheduling for a smart factory using a reinforcement learning approach.

LineFlow: A Framework to Learn Active Control of Production Lines Real-time scheduling for a smart factory using a reinforcement learning approach

Reference 44

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.478642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.342808Z digest=sha256:8960d9f51d227ef55be7e1d6b4824b0ae199d805125222df8e3cc5123448b811

Observation 185aa2ec-7314-4bf2-a5fa-69f4e69cb48c · outbound

This paper cites J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al.

LineFlow: A Framework to Learn Active Control of Production Lines J., Guez, A., Sifre, L., Van Den Driessche, G., Schrittwieser, J., Antonoglou, I., Panneershelvam, V., Lanctot, M., et al

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.347063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.347063Z digest=sha256:9c87855da09d5d7171ff3067365d08445d1bae6cf992adb2b9444fe81d0d2c25

Observation 091f7f73-3fbc-4f14-bd47-4ca5dbfe56de · outbound

This paper cites Simpy 4.1 webpage, 2025.

LineFlow: A Framework to Learn Active Control of Production Lines Simpy 4.1 webpage, 2025

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.626798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.351118Z digest=sha256:0369aeadf91efe37c160d15d240e0caf1e973290f80112073232b4b698b11db9

Observation 0eaa4b93-0667-4767-8f23-0a512773590b · outbound

This paper cites A., Th \"u rer, M., and Chang, Q.

LineFlow: A Framework to Learn Active Control of Production Lines A., Th \"u rer, M., and Chang, Q

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.612671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.355146Z digest=sha256:edfbf10468a4694507e0df28eaadd76a8f220c105c2f3b03cc6a3e8f20b594d3

Observation 7c486446-448f-4eac-8b38-0cfec5872a30 · outbound

This paper cites an unresolved cited work.

LineFlow: A Framework to Learn Active Control of Production Lines Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-15T22:40:00.598097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.359601Z digest=sha256:5f8e78fb2588a989252b104859bc9aff0372e53b92b97d0e127301fc90966b0e

Observation 6a0eb2d9-384e-4191-ba91-22c1d90f6f78 · outbound

This paper cites and Chauhan, S.

LineFlow: A Framework to Learn Active Control of Production Lines and Chauhan, S

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.363604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.363604Z digest=sha256:23d644bcb3d9453d0ab9ff7e132841f200354907f0e15ecad5a3a45d714d88e9

Observation 99384850-70fc-4fe3-acd4-880a706bdc72 · outbound

This paper cites A parallel deep reinforcement learning framework for controlling industrial assembly lines.

LineFlow: A Framework to Learn Active Control of Production Lines A parallel deep reinforcement learning framework for controlling industrial assembly lines

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.368116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.368116Z digest=sha256:7e67fb5dd60091bd31d49bf4ee7d32327d644fb574d44a4632e58faf6f47e0a8

Observation 4c57a98a-ed1b-4b0e-bb05-6cbde7770ec0 · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

LineFlow: A Framework to Learn Active Control of Production Lines Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.372428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.372428Z digest=sha256:92bd7069cc206bb1545deef57880395efb1354db3cfa6abf0e553d028f987235

Observation 26537d3d-1234-4143-8c7f-7f802c2496f5 · outbound

This paper cites an unresolved cited work.

LineFlow: A Framework to Learn Active Control of Production Lines Unresolved cited work

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.377749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.377749Z digest=sha256:8d1af4cff12038f62d0d40a4dd297dab8eb4946650f8138e4c64774e3877e5ad

Observation ed8096bd-d018-4bd9-9ebf-78e959c1b15b · outbound

This paper cites M., Mathieu, M., Dudzik, A., Chung, J., Choi, D.

LineFlow: A Framework to Learn Active Control of Production Lines M., Mathieu, M., Dudzik, A., Chung, J., Choi, D

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.382814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.382814Z digest=sha256:a0e514f61ddede3347f992735e97caaf833d60b4542f1f84acdd603fa67084bc

Observation f9aa09b4-bf25-4362-99b4-cfe810357212 · outbound

This paper cites Multi-agent reinforcement learning based maintenance policy for a resource constrained flow line system.

LineFlow: A Framework to Learn Active Control of Production Lines Multi-agent reinforcement learning based maintenance policy for a resource constrained flow line system

Reference 54

Resolution
verified exact
doi, observed 2026-08-15T22:39:59.446170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.386972Z digest=sha256:d205e41573c0c40ac80a2d96bd8c3b85c40c98932a25fec602be4da50c17501c

Observation 24aba305-2c6f-479a-8a1f-a01807938f04 · outbound

This paper cites D ata S tructures for S tatistical C omputing in P ython.

LineFlow: A Framework to Learn Active Control of Production Lines D ata S tructures for S tatistical C omputing in P ython

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-15T22:39:59.391495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:39:59.391495Z digest=sha256:0ed6b9ffd1da5884ee5e495383483b830a3fbb1404309b7c791af4673e1b44de

Observation 8b2dd161-baeb-432c-885f-12eb59d3c9e2 · outbound

This paper cites Daydreamer: World models for physical robot learning.

LineFlow: A Framework to Learn Active Control of Production Lines Daydreamer: World models for physical robot learning

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:40:00.575195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.395660Z digest=sha256:2730a7aebcaa747e1a93509ea018f4546c8e3a62ba6360167d0797a04cedaab6

Observation d074f798-9f3c-4b24-a337-5cb478bb1a2a · outbound

This paper cites and Lan, R.

LineFlow: A Framework to Learn Active Control of Production Lines and Lan, R

Reference 57

Resolution
metadata mismatch
raw_fallback, observed 2026-08-15T22:39:59.799717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T22:39:59.399768Z digest=sha256:1b5a200dad1bdbac1714d75458571760c0cb9d3839a5e603b7814eb652d33a9b

Pith citing papers

No inbound Pith citation observations are available.