Paper Citation Record · LEDGER

Quantum reinforcement learning in dynamic environments

As of 9 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 2 inbound Pith citation observations for arXiv:2507.01691.

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

pith.paper-citation-record.v1
2507.01691 v1

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:53:53.890488Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:36:11.767803Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T04:53:58.087145Z

Reference resolution

61 of 61 outbound references displayed

verified exact13
verified fuzzy10
unresolved35
parse uncertain0
malformed identifier1
metadata mismatch2

External citation measurements

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Outbound references

Observation 353c3696-d164-4c89-a8d3-bc72eeb1ad18 · outbound

This paper cites , Barreto , A.

Quantum reinforcement learning in dynamic environments , Barreto , A

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:58.165576Z

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Observation 955973a7-3e84-4d5b-b378-136d2f67e920 · outbound

This paper cites , Brassard , G.

Quantum reinforcement learning in dynamic environments , Brassard , G

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.263694Z

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Observation 14461d0e-3afb-420c-ad4c-4cfde6f6478e · outbound

This paper cites , H yer , P.

Quantum reinforcement learning in dynamic environments , H yer , P

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.344854Z

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Observation cc62b7b6-5f73-44e8-a0d3-e069e273b93c · outbound

This paper cites , Cuevas , G.

Quantum reinforcement learning in dynamic environments , Cuevas , G

Reference 4

Resolution: verified exact; doi, observed 2026-08-06T20:53:55.633462Z

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Observation 2237459c-c656-48c7-ae24-14242d3920ac · outbound

This paper cites , Arrasmith , A.

Quantum reinforcement learning in dynamic environments , Arrasmith , A

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.498052Z

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Observation 029b77e2-f599-4105-8035-db0a7f97ca51 · outbound

This paper cites Does provable absence of barren plateaus imply classical simulability?.

Quantum reinforcement learning in dynamic environments Does provable absence of barren plateaus imply classical simulability?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.562993Z

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Observation d3744512-e590-4679-a5cd-47e66fc515e7 · outbound

This paper cites , Yang , C.-H.H.

Quantum reinforcement learning in dynamic environments , Yang , C.-H.H

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.616688Z

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Observation ef5573ed-becf-4741-a15e-2370e3302ac0 · outbound

This paper cites , Chang , Y.-J.

Quantum reinforcement learning in dynamic environments , Chang , Y.-J

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.683869Z

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Observation 7ab6526e-5e7d-44f3-9d89-b72f76b889d2 · outbound

This paper cites , Kerenidis , I.

Quantum reinforcement learning in dynamic environments , Kerenidis , I

Reference 9

Resolution: verified exact; doi, observed 2026-08-06T20:53:55.486535Z

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Observation afad38c7-5e8b-4387-9a56-bc120ceefb7c · outbound

This paper cites , Yeung , D.-Y.

Quantum reinforcement learning in dynamic environments , Yeung , D.-Y

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:58.027833Z

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

Observation 6c20d084-571f-4c46-9916-d60d1ffd07e6 · outbound

This paper cites , Rocchetto , A.

Quantum reinforcement learning in dynamic environments , Rocchetto , A

Reference 11

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Observation 62c5b979-489f-4188-baac-00c9f1e5b65e · outbound

This paper cites , Meier , U.

Quantum reinforcement learning in dynamic environments , Meier , U

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:49.947876Z

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Observation b4bbc6a0-0edf-4414-abba-69a8b0244296 · outbound

This paper cites , Buffoni , L.

Quantum reinforcement learning in dynamic environments , Buffoni , L

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.027441Z

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Observation c3212aff-df09-45b1-9da5-5d0d1fab3590 · outbound

This paper cites , Chen , C.

Quantum reinforcement learning in dynamic environments , Chen , C

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.106694Z

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Observation 782a178f-564d-413f-b78a-09656ed33ad7 · outbound

This paper cites , Taylor , J.M.

Quantum reinforcement learning in dynamic environments , Taylor , J.M

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.158504Z

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Observation 44f38714-7a9a-4ea5-a902-9f374b1535ab · outbound

This paper cites Exponential improvements for quantum-accessible reinforcement learning.

Quantum reinforcement learning in dynamic environments Exponential improvements for quantum-accessible reinforcement learning

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:53:56.660236Z

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Observation b0451e22-e228-41b0-8969-b9c5be9c7662 · outbound

This paper cites , Abbeel , P.

Quantum reinforcement learning in dynamic environments , Abbeel , P

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.868746Z

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

Observation db3d71df-13c9-46a0-97c4-0eccd66cd76e · outbound

This paper cites Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning.

Quantum reinforcement learning in dynamic environments Quantum Computing Provides Exponential Regret Improvement in Episodic Reinforcement Learning

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-08-06T20:53:56.535115Z

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

Observation 2edad1c7-b56f-42f5-8573-ca0a1eccbb5f · outbound

This paper cites On the relation between trainability and dequantization of variational quantum learning models.

Quantum reinforcement learning in dynamic environments On the relation between trainability and dequantization of variational quantum learning models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.410029Z

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Observation 46f4b87a-7b86-4aa0-8164-b2f002be4c5a · outbound

This paper cites : Quantum mechanics helps in searching for a needle in a haystack.

Quantum reinforcement learning in dynamic environments : Quantum mechanics helps in searching for a needle in a haystack

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.479436Z

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Observation b3643d83-f85b-4755-9767-336d5e1a075a · outbound

This paper cites , Dunjko , V.

Quantum reinforcement learning in dynamic environments , Dunjko , V

Reference 21

Resolution: verified exact; doi, observed 2026-08-06T20:53:55.347003Z

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 d7c9e87c-d743-407c-9e3a-c8db73e00879 · outbound

This paper cites , W \"o lk , S.

Quantum reinforcement learning in dynamic environments , W \"o lk , S

Reference 22

Resolution: verified exact; doi, observed 2026-08-06T20:53:55.198241Z

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

Observation 78d4e288-6e8b-4827-a920-2b06ef1336fd · outbound

This paper cites , Gyurik , C.

Quantum reinforcement learning in dynamic environments , Gyurik , C

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.712455Z

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

Observation 6d5184e5-4433-4925-8af7-488cc76fa548 · outbound

This paper cites , Trenkwalder , L.M.

Quantum reinforcement learning in dynamic environments , Trenkwalder , L.M

Reference 24

Resolution: verified exact; doi, observed 2026-08-06T20:53:55.036498Z

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Observation 6bef48a9-503d-44ff-bee1-3dc25f646107 · outbound

This paper cites , Riemer , M.

Quantum reinforcement learning in dynamic environments , Riemer , M

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.799756Z

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Observation 1674c910-c3aa-4f88-b66a-003d4c04dfb9 · outbound

This paper cites , Sutskever , I.

Quantum reinforcement learning in dynamic environments , Sutskever , I

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.884301Z

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Observation d13f9c2f-48eb-4b7c-bcfb-eb1d5920cfda · outbound

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

Quantum reinforcement learning in dynamic environments Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:50.948259Z

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Observation e95f4ef8-8896-4499-b714-9d3dbe563874 · outbound

This paper cites Continuous control with deep reinforcement learning.

Quantum reinforcement learning in dynamic environments Continuous control with deep reinforcement learning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.000022Z

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Observation 7f5fda6e-27e9-439d-9faf-cd33575f6701 · outbound

This paper cites , Arunachalam , S.

Quantum reinforcement learning in dynamic environments , Arunachalam , S

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.052747Z

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Observation c2dc4a57-ef15-4a3d-8450-b5bada63572c · outbound

This paper cites , Si , M.

Quantum reinforcement learning in dynamic environments , Si , M

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.558082Z

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

Observation 9e60453b-79d8-4546-b0d9-cd61ff66bfa5 · outbound

This paper cites , Si , M.

Quantum reinforcement learning in dynamic environments , Si , M

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.215843Z

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Observation a330f1a2-7879-4b16-84de-a7f45176f5fa · outbound

This paper cites , Makmal , A.

Quantum reinforcement learning in dynamic environments , Makmal , A

Reference 32

Resolution: verified exact; doi, observed 2026-08-06T20:53:54.877334Z

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

Observation 5410c872-e49b-4dc2-b2fe-1e20b5c1ed80 · outbound

This paper cites , Cohen , N.J.

Quantum reinforcement learning in dynamic environments , Cohen , N.J

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.353953Z

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Observation e99eca3c-c72c-425a-a24a-704bcf214ea5 · outbound

This paper cites , Makmal , A.

Quantum reinforcement learning in dynamic environments , Makmal , A

Reference 34

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:53:56.386391Z

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

Observation 60b8c208-528c-4de4-b8d4-b7569320cf65 · outbound

This paper cites , Scherer , D.D.

Quantum reinforcement learning in dynamic environments , Scherer , D.D

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.479576Z

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Observation 0ee2d3a6-cb7f-4f35-9a87-55a4a4924d4f · outbound

This paper cites , Kavukcuoglu , K.

Quantum reinforcement learning in dynamic environments , Kavukcuoglu , K

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.565011Z

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Observation f436015a-a989-4c25-9557-b481d162b133 · outbound

This paper cites Exponential quantum advantages in learning quantum observables from classical data.

Quantum reinforcement learning in dynamic environments Exponential quantum advantages in learning quantum observables from classical data

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.652640Z

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Observation 75c4d79f-5ecc-491a-8033-a5cb7c0a2c39 · outbound

This paper cites : A survey of reinforcement learning algorithms for dynamically varying environments.

Quantum reinforcement learning in dynamic environments : A survey of reinforcement learning algorithms for dynamically varying environments

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:51.725748Z

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Observation 62f7310b-4f02-4d29-be8e-6a6d63b000b5 · outbound

This paper cites , Dunjko , V.

Quantum reinforcement learning in dynamic environments , Dunjko , V

Reference 39

Resolution: verified exact; doi, observed 2026-08-06T20:53:54.668985Z

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

Observation 86015ffb-5129-418a-ab5f-49dde5ad5e7d · outbound

This paper cites , Wiering , M.A.

Quantum reinforcement learning in dynamic environments , Wiering , M.A

Reference 40

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T20:53:56.044520Z

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Observation ce160d58-29aa-43de-80f4-9384b9087661 · outbound

This paper cites : Quantum computing in the NISQ era and beyond.

Quantum reinforcement learning in dynamic environments : Quantum computing in the NISQ era and beyond

Reference 41

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Observation e4eed36f-c9ed-4f26-9521-4ec8782e9f28 · outbound

This paper cites : Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1st edn.

Quantum reinforcement learning in dynamic environments : Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1st edn

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.423926Z

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Observation f3c39c8b-79e7-4965-a2ed-312a537115ef · outbound

This paper cites : Continual learning in reinforcement environments.

Quantum reinforcement learning in dynamic environments : Continual learning in reinforcement environments

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.304850Z

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Observation 8e3e1632-3a8a-4d89-894e-15a5fef20b11 · outbound

This paper cites o mberg , T. , Schiansky , P. , Dunjko , V. , Friis , N. , Harris , N.C. , Hochberg , M. , Englund , D. , W \.

Quantum reinforcement learning in dynamic environments o mberg , T. , Schiansky , P. , Dunjko , V. , Friis , N. , Harris , N.C. , Hochberg , M. , Englund , D. , W \

Reference 44

Resolution: verified exact; doi, observed 2026-08-06T20:53:54.459517Z

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

Observation e85885c9-174d-49bb-84d1-24f6ec28ff85 · outbound

This paper cites , Antonoglou , I.

Quantum reinforcement learning in dynamic environments , Antonoglou , I

Reference 45

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Observation 6388860c-6b02-4516-8ceb-2979e41349ac · outbound

This paper cites , Killoran , N.

Quantum reinforcement learning in dynamic environments , Killoran , N

Reference 46

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Observation 0c9ae239-994e-48b8-a92a-f0e2da881216 · outbound

This paper cites , W \"o lk , S.

Quantum reinforcement learning in dynamic environments , W \"o lk , S

Reference 47

Resolution: verified exact; doi, observed 2026-08-06T20:53:54.332661Z

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

Observation 0df5869b-0779-4bf7-8b0d-1bad1f827bdc · outbound

This paper cites : Algorithms for quantum computation: discrete logarithms and factoring.

Quantum reinforcement learning in dynamic environments : Algorithms for quantum computation: discrete logarithms and factoring

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:52.527616Z

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Observation 78abdd38-7987-4232-96df-342d26cc93fc · outbound

This paper cites , Basso , E.W.

Quantum reinforcement learning in dynamic environments , Basso , E.W

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:52.598401Z

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Observation e7c445af-f3d1-490a-a108-1d87e2f1ebaf · outbound

This paper cites , Jerbi , S.

Quantum reinforcement learning in dynamic environments , Jerbi , S

Reference 50

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Observation 4e6be170-b738-4e3c-9b5f-c927b012d8a7 · outbound

This paper cites , Weiss , E.

Quantum reinforcement learning in dynamic environments , Weiss , E

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.168486Z

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

Observation 59147d27-28a7-4caf-9de9-cef62352dade · outbound

This paper cites , W \"o lk , S.

Quantum reinforcement learning in dynamic environments , W \"o lk , S

Reference 52

Resolution: verified exact; doi, observed 2026-08-06T20:53:54.199744Z

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

Observation aca432a3-74e6-48a4-96d6-6bda11498163 · outbound

This paper cites , Barto , A.G.

Quantum reinforcement learning in dynamic environments , Barto , A.G

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:57.029628Z

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

Observation 7d8c3af7-7cf0-4305-b35d-397c0a360eb9 · outbound

This paper cites , Shazeer , N.

Quantum reinforcement learning in dynamic environments , Shazeer , N

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T20:53:56.907107Z

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Observation 28b4a498-04c2-4693-9ec1-9ab0f459b858 · outbound

This paper cites , Dayan , P.

Quantum reinforcement learning in dynamic environments , Dayan , P

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:53.358936Z

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Observation 16debd30-cc57-4326-94f8-eea268b67d4f · outbound

This paper cites Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learning.

Quantum reinforcement learning in dynamic environments Quantum Policy Iteration via Amplitude Estimation and Grover Search -- Towards Quantum Advantage for Reinforcement Learning

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:53.445777Z

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Observation 2cd75ace-30f7-4ae8-9e87-97579b73dc62 · outbound

This paper cites : Simple statistical gradient-following algorithms for connectionist reinforcement learning.

Quantum reinforcement learning in dynamic environments : Simple statistical gradient-following algorithms for connectionist reinforcement learning

Reference 57

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Observation d65a9081-75b0-42aa-95ec-22759b26015a · outbound

This paper cites , Jin , S.

Quantum reinforcement learning in dynamic environments , Jin , S

Reference 58

Resolution: verified exact; doi, observed 2026-08-06T20:53:54.070042Z

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

Observation ababe30b-1db1-4bb3-947b-19622a51b47c · outbound

This paper cites Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret.

Quantum reinforcement learning in dynamic environments Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:53.706900Z

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Observation b4038d34-0650-4519-9b81-f71ca1e88fda · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Quantum reinforcement learning in dynamic environments Fine-Tuning Language Models from Human Preferences

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-06T20:53:53.781669Z

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Observation b7a1847b-9d24-45d1-9dab-745360ae442b · outbound

This paper cites write newline.

Quantum reinforcement learning in dynamic environments write newline

Reference 61

Resolution: malformed identifier; no resolver link, observed 2026-08-06T20:53:53.890488Z

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Pith citing papers

Observation 59b9ada6-54ca-4ecf-b770-98fa0d460cfe · inbound

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation cites this paper.

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation Quantum reinforcement learning in dynamic environments

Reference 27

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Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation cites this paper.

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation Quantum reinforcement learning in dynamic environments

Reference 27

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