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Paper Citation Record · LEDGER

Quantum reinforcement learning in dynamic environments

As of 7 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 2026-08-07T06:34:17.273281+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

No source-named external measurement is stored.

Outbound references

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

This paper cites , Barreto , A.

Quantum reinforcement learning in dynamic environments , Barreto , A

Reference 1

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:49.204165Z digest=sha256:55359ecdee4eb9526990b4b9b6aa93247a3b0bde8e4832d4dc17501b28849dc5

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

This paper cites , Brassard , G.

Quantum reinforcement learning in dynamic environments , Brassard , G

Reference 2

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

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source=arxiv_source observed=2026-08-06T20:53:49.263694Z digest=sha256:8536e60f024ccd266610f6ced18e99868ad636ec3e3cd8f0d83f6e48662614c8

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

This paper cites , H yer , P.

Quantum reinforcement learning in dynamic environments , H yer , P

Reference 3

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source=arxiv_source observed=2026-08-06T20:53:49.344854Z digest=sha256:792f3f881fea53f110577452eddbf62987bec59bfdc270bd624524d969d57970

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

This paper cites , Cuevas , G.

Quantum reinforcement learning in dynamic environments , Cuevas , G

Reference 4

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doi, observed 2026-08-06T20:53:55.633462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:49.430788Z digest=sha256:745696524adc727377d0a473295b1898b897503f22a61431450ef34f45d8a283

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

This paper cites , Arrasmith , A.

Quantum reinforcement learning in dynamic environments , Arrasmith , A

Reference 5

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

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source=arxiv_source observed=2026-08-06T20:53:49.498052Z digest=sha256:d709ad7863793e7a21e78ba07f2eb8f76bda4ee689bb17d8da7db1feec29b939

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

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source=arxiv_source observed=2026-08-06T20:53:49.562993Z digest=sha256:0fffa37f64db66219c7259b88ded199eb883551752e2cbe29b228db99fda67e5

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

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

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source=arxiv_source observed=2026-08-06T20:53:49.616688Z digest=sha256:9a291edb10b3f6a9d0d1a49b55bd3faa0e0559dfb5164fca8ae1210aa5778eef

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

This paper cites , Chang , Y.-J.

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

Reference 8

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

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source=arxiv_source observed=2026-08-06T20:53:49.683869Z digest=sha256:2c9dd7047ea6842121f6f3cf5a7b9e2ad43d19e255cdecc5947ceaac9b7696e6

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

This paper cites , Kerenidis , I.

Quantum reinforcement learning in dynamic environments , Kerenidis , I

Reference 9

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:49.742903Z digest=sha256:12fca328a5d841676a7ef50385148c7f7e7a3b335ff3590143d04e660692b0c1

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

This paper cites , Yeung , D.-Y.

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

Reference 10

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raw_fallback, observed 2026-08-06T20:53:58.027833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:49.812620Z digest=sha256:105cdd4c3eaf5a88b3c9340f8d6c676341b2c1ffdd84464aefbe51add88cb5a4

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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source=arxiv_source observed=2026-08-06T20:53:49.892361Z digest=sha256:0918e6def84596f94bc67918169044aef8cd16367c6dd7a35984af93053207fc

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

This paper cites , Meier , U.

Quantum reinforcement learning in dynamic environments , Meier , U

Reference 12

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source=arxiv_source observed=2026-08-06T20:53:49.947876Z digest=sha256:1370b31514726afc7a02a29bab71aab4a832400d8a4e20a1d2187aa7923c9bd5

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

This paper cites , Buffoni , L.

Quantum reinforcement learning in dynamic environments , Buffoni , L

Reference 13

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source=arxiv_source observed=2026-08-06T20:53:50.027441Z digest=sha256:72c400d8e562634b6c118e1b7452b48da61eb33b95abd231f30db6bbb76b2166

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

This paper cites , Chen , C.

Quantum reinforcement learning in dynamic environments , Chen , C

Reference 14

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source=arxiv_source observed=2026-08-06T20:53:50.106694Z digest=sha256:733bde495a604f7658853edf16bafba8ee73fdaeeb086df8fb3156455dff60e6

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

This paper cites , Taylor , J.M.

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

Reference 15

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source=arxiv_source observed=2026-08-06T20:53:50.158504Z digest=sha256:cc126420c6d5395a006a1866b6247a05fe91e698fcc86de23db1a066d225765d

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

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local_arxiv, observed 2026-08-06T20:53:56.660236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.229737Z digest=sha256:2118de99ef94848ff6c8b93e690ab4ca52692f4ae7dd5bbb18c796086d3adb37

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

This paper cites , Abbeel , P.

Quantum reinforcement learning in dynamic environments , Abbeel , P

Reference 17

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.296449Z digest=sha256:d972360580c1b4b9ca01aec3d14f35aeb7fda8efbdcf954a95c5037457456558

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

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local_arxiv, observed 2026-08-06T20:53:56.535115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.355747Z digest=sha256:5920bb5e48d769ba484e99f95d709be8dc17e6d88b38c3ff5e1fd0f5b57204af

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

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source=arxiv_source observed=2026-08-06T20:53:50.410029Z digest=sha256:1becb7a21d45852ff1c48010babfee3f0e495fd4e533c23bb381b5fa03a16a0c

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

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source=arxiv_source observed=2026-08-06T20:53:50.479436Z digest=sha256:e7ec4bf45641376d3673537618d884b848130256db7b824e9f56cb66566cd8b8

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

This paper cites , Dunjko , V.

Quantum reinforcement learning in dynamic environments , Dunjko , V

Reference 21

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doi, observed 2026-08-06T20:53:55.347003Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.535114Z digest=sha256:6d73c8858f804e59eab7aa84849fbb90a9051b911d1c5909f402ec5f8a7ef325

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

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doi, observed 2026-08-06T20:53:55.198241Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.594674Z digest=sha256:efb302f66b5241912fc7a22cb3e414900ab716daf9a2f0c98caf560543c742f6

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

This paper cites , Gyurik , C.

Quantum reinforcement learning in dynamic environments , Gyurik , C

Reference 23

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raw_fallback, observed 2026-08-06T20:53:57.712455Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.659248Z digest=sha256:77d0fecca1d0b58f17a44588c7c26d84cd14335d2fae1439fbd4299123f1e38d

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

This paper cites , Trenkwalder , L.M.

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

Reference 24

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:50.734170Z digest=sha256:1f829b4d23649217312f9435fb854ee65b7c8fd6a86038a34d5c3b75cf4cd160

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

This paper cites , Riemer , M.

Quantum reinforcement learning in dynamic environments , Riemer , M

Reference 25

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source=arxiv_source observed=2026-08-06T20:53:50.799756Z digest=sha256:4ad7408f644f199528602e796dcca4ff70760b14739c57f9ab90c680cde2b404

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

This paper cites , Sutskever , I.

Quantum reinforcement learning in dynamic environments , Sutskever , I

Reference 26

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source=arxiv_source observed=2026-08-06T20:53:50.884301Z digest=sha256:893d9dd9ab9a0f420590412748baba23fabd212885f606dae28b413fa1b6570d

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

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source=arxiv_source observed=2026-08-06T20:53:50.948259Z digest=sha256:daaad5649e62ecdac1e9fb7c4ff419f0e235b1fc9694e2f9b47fe8f4069d03fe

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

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source=arxiv_source observed=2026-08-06T20:53:51.000022Z digest=sha256:5bcd035e4d6d67a5db15fe94148d488ee5c40fc3592ac37ba27f362f2bb45663

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

This paper cites , Arunachalam , S.

Quantum reinforcement learning in dynamic environments , Arunachalam , S

Reference 29

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source=arxiv_source observed=2026-08-06T20:53:51.052747Z digest=sha256:a1ba8d5298836d8bd72bd94ccec9e612a14b0d0dbb6547f42f2a7625a80f3eb5

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

This paper cites , Si , M.

Quantum reinforcement learning in dynamic environments , Si , M

Reference 30

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raw_fallback, observed 2026-08-06T20:53:57.558082Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:51.141244Z digest=sha256:98bf14c58ddf4f50e74909a2af0bc4e3125a5f117ed7439d7c72ea986c50362f

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

This paper cites , Si , M.

Quantum reinforcement learning in dynamic environments , Si , M

Reference 31

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source=arxiv_source observed=2026-08-06T20:53:51.215843Z digest=sha256:adbf0569310051c280e8a7280da1ae2165e06e514b343ec827537b59b367e285

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

This paper cites , Makmal , A.

Quantum reinforcement learning in dynamic environments , Makmal , A

Reference 32

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doi, observed 2026-08-06T20:53:54.877334Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:51.275869Z digest=sha256:a70dd1828cc2ea3743788693d87e06d0a77f72925785ad2929b89eb9b0ebef02

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

This paper cites , Cohen , N.J.

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

Reference 33

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source=arxiv_source observed=2026-08-06T20:53:51.353953Z digest=sha256:d27fed92b5195aaca86326cbb669731cb50186f455ce1e94c2721f9fc2c6d83e

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

This paper cites , Makmal , A.

Quantum reinforcement learning in dynamic environments , Makmal , A

Reference 34

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raw_fallback, observed 2026-08-06T20:53:56.386391Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:51.423143Z digest=sha256:c7a078b8e2f4ff2bc59014432bc0991df13700b6dfcd884012834432246ce1a2

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

This paper cites , Scherer , D.D.

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

Reference 35

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source=arxiv_source observed=2026-08-06T20:53:51.479576Z digest=sha256:36077e789a57adb5b1d39b5c2d94ae12d3d323d22e4379acc9a7065ab0a1d92b

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

This paper cites , Kavukcuoglu , K.

Quantum reinforcement learning in dynamic environments , Kavukcuoglu , K

Reference 36

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source=arxiv_source observed=2026-08-06T20:53:51.565011Z digest=sha256:560e640046e5bc5566e288586033050379fe03b873574bd0856c29a09f212a99

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

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source=arxiv_source observed=2026-08-06T20:53:51.652640Z digest=sha256:80588934164b23acc11ce7efda3a57db4974589272f8c03b4ca375a881d3f8c7

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

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source=arxiv_source observed=2026-08-06T20:53:51.725748Z digest=sha256:7686e8e6857934cdde119a2af385fa0624ac9983682729ca8c0c03bd03116e6f

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

This paper cites , Dunjko , V.

Quantum reinforcement learning in dynamic environments , Dunjko , V

Reference 39

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doi, observed 2026-08-06T20:53:54.668985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:51.787914Z digest=sha256:8d2717684d145297279dc314bedbad64cfc5be40a33b654f6d02ce3825be3c1d

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

This paper cites , Wiering , M.A.

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

Reference 40

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raw_fallback, observed 2026-08-06T20:53:56.044520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:51.867799Z digest=sha256:6efba234a8686f40d8a677674e4b89ea67e931227e451ffb1307a1d70824d986

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:51.931627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:51.931627Z digest=sha256:5287537b2f0062e993a40431b2bfcf1ab37d0a7e87db93638633d97f30f9c605

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

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:52.006742Z digest=sha256:cd32a4805f5b57281f7ad7e9dafa73b85b9b1acc542cf8740dca85be07cfa9bc

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:52.089925Z digest=sha256:2feee97fe1e5ff9add037243f6d5ec769c8017d9d9959a52131e7bed69df58d4

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:52.157831Z digest=sha256:0f55fddea204950e3a18e738f75eeda51872ef904ee094ed9d4c923435b90b8b

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

This paper cites , Antonoglou , I.

Quantum reinforcement learning in dynamic environments , Antonoglou , I

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:52.226743Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:52.226743Z digest=sha256:1c5a8c4f3c2ad81931461f9f1ff212319c78f717b8aa9221ff6eb13cf5798a37

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

This paper cites , Killoran , N.

Quantum reinforcement learning in dynamic environments , Killoran , N

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:52.336904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:52.336904Z digest=sha256:6618551057ca95f6ab2e8753ab9318527e7f299b3a1312b18b8317bef6dd22b2

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:52.432616Z digest=sha256:78619d916d003871493e049184c0d020c55e29c47b2e503689a5615c001bf876

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:52.527616Z digest=sha256:1cbefe477f8edebabd2ccf6dd53cc5eb0016207c7fa95e8aaeea83326fa3b7d4

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:52.598401Z digest=sha256:dd74e3271dad6e2b20610e3e0e8dce26bd0242473fd8d99c69140706933eaccb

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

This paper cites , Jerbi , S.

Quantum reinforcement learning in dynamic environments , Jerbi , S

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:52.682047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:52.682047Z digest=sha256:c3f2f720f42d426efe99411e181a3646e8b0db3837fdbb06e82c5094aa9ef219

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:52.843181Z digest=sha256:b6a7376480d198568068ddd31daa312e4cffe0cf2a45c4a860fb455cbf0d70d8

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:52.964122Z digest=sha256:d78ea64bb39eefd7406489f334d52b2cb350e6d20a67d2189831870621ac395e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:53.125676Z digest=sha256:61bd3a14e3c8c0a40346c540b7eb34efcf679b440d9444d3cbbb81e0b6048522

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:53.264533Z digest=sha256:9ae4c76bd6e779ba53d1f0a2e2ab1d2fc38a236eeb2831aa354aafa0c12b18d2

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.358936Z digest=sha256:d3737ef981b6c95913eb868417ad9df83ecf0419461801f7aae3d117eb64c2da

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.445777Z digest=sha256:9a382716d11618ca47f5797d3a97ef8ff70e3e896007e76dd164166c9d22c9b6

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

Resolution
unresolved
no resolver link, observed 2026-08-06T20:53:53.517354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.517354Z digest=sha256:97fb5108f1a6f780aa6f66f4453f51bf12c43a713cf386b5f0fbcf05fc2c99d7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T20:53:53.616842Z digest=sha256:c800e5741445e263c19166ddac4b26670d21cb8402eb84346d7b360e4a0568e1

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.706900Z digest=sha256:720e257f61ded97dbbf7f6326eac5f5ee113315946dd8ee6fd90186f821162e7

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.781669Z digest=sha256:eb03ded9cd4e764b5daa86c94a8b27a49a4cbe615c08128e02fcb7b93a4abc76

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:53:53.890488Z digest=sha256:8c8df39a419c7b571ac1faf618310ade48fdddf8b4477fed18b57ef921f9a18d

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

Resolution
verified exact
arxiv_id, observed 2026-05-21T04:53:58.088564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T04:50:37.976670Z digest=sha256:e2201bedbd406a727cd5636600824998a0d3cdff9b1d54bb06313e5f92ebf937

Observation fc056375-29f7-4295-ad73-149d1e28b357 · 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

Resolution
unresolved
no resolver link, observed 2026-08-02T13:36:11.767803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:36:11.767803Z digest=sha256:7da2b1399ba1c76ebbb52394dc1071b14b319b148d680f1d70f21377c3a909e4