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Paper Citation Record · LEDGER

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity

As of 9 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2602.03778.

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

pith.paper-citation-record.v1
2602.03778 v2

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:00:44.567451Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T19:31:33.732451Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T22:50:51.108083Z

Reference resolution

49 of 49 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c55ad402-e7f1-4ec4-9a86-8f19abcee506 · outbound

This paper cites Andrychowicz, F.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Andrychowicz, F

Reference 1

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source=pdf_text observed=2026-08-03T05:00:39.290410Z digest=sha256:66204ec00fabf8151cbb7c847f199fe5db47a83619eba19142e3b02c733eb1e7

Observation d3087eee-dc31-4e4f-ba50-d8ad8ffafe9e · outbound

This paper cites Predictive CVar q-learning.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Predictive CVar q-learning

Reference 2

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source=pdf_text observed=2026-08-03T05:00:39.361929Z digest=sha256:b0167dd47fe1f3ba6913e5dd368a08c4828f2b17faf58e79a1d694ba16936a2d

Observation 94a3ad6c-89c4-42ac-984e-440514776dad · outbound

This paper cites Artzner, F.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Artzner, F

Reference 3

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source=pdf_text observed=2026-08-03T05:00:39.466284Z digest=sha256:f5c1e90a356d3c5e491ae047edcf9778a11d57d4c9885cb7ce2abc28e0089862

Observation 8aa3ed2d-c9fd-4f5d-972f-dc515628d835 · outbound

This paper cites Bastani, J.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Bastani, J

Reference 4

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source=pdf_text observed=2026-08-03T05:00:39.607989Z digest=sha256:bc29906792f37ca4e7e8c83fb2893eca81ce035333555830b7ff05244eff5b31

Observation aebb6ee5-4c59-442f-944a-13d251065b75 · outbound

This paper cites B¨ auerle, T.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity B¨ auerle, T

Reference 5

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source=pdf_text observed=2026-08-03T05:00:39.684832Z digest=sha256:c14ba3a329c086cf38532e0ec77601783aa4f8e028e5053ba2dfc20e83d5c090

Observation adc529bf-d9bb-4f87-abb0-07152ad8ed42 · outbound

This paper cites B¨ auerle and J.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity B¨ auerle and J

Reference 6

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source=pdf_text observed=2026-08-03T05:00:39.836318Z digest=sha256:9ba7c804004558c9f9b243f5e24143cc090c7b0ee1fef0cd3ff370f14bc0f53c

Observation bbb662eb-9be9-406f-82af-19d94cf73309 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 7

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source=pdf_text observed=2026-08-03T05:00:39.953096Z digest=sha256:701282bed1d6870309f1ce893bcaf337e7d2c765e40055d9b6263281874f70c1

Observation 00f0eb34-09fa-4a1c-afce-0493d9337f7b · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-03T05:00:40.111565Z digest=sha256:d8222d10679e474b5722075806eafde6987defe75fd83848d8428bdec198aa2e

Observation c61a1492-e09f-4179-ac3d-c1e89001b2bb · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 9

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source=pdf_text observed=2026-08-03T05:00:40.257543Z digest=sha256:f6c1ae2c93899703d0505a36a45a14f144764754da8a27609e5f927d3f073535

Observation dd488dd3-4cc2-430d-9e21-05ed71bb3142 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 10

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source=pdf_text observed=2026-08-03T05:00:40.458999Z digest=sha256:f169f650913dbbc089571bc83add5ee9f3c3ddfa785c288c4565909dc79537a4

Observation 9956550a-6198-422e-a856-d83fd58a94da · outbound

This paper cites Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping

Reference 11

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source=pdf_text observed=2026-08-03T05:00:40.609467Z digest=sha256:c062e300632a4e4cdebd6b99c7b912b9ca4cbae2e3141de957cbd62e555b151d

Observation 5f580598-567a-4631-a287-682c3a47787e · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-03T05:00:40.760225Z digest=sha256:62ec5aef6da7ff3a123e68fe1d5fbd66bb225eefa30643bd74982992bb6d59f0

Observation f8e1c3c3-b51c-4b3c-b049-10b63b7b72b6 · outbound

This paper cites Coache and S.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Coache and S

Reference 13

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source=pdf_text observed=2026-08-03T05:00:40.908153Z digest=sha256:67db66de4b15449f995328f1f72d936f6cfca5098b39e29b78e230bdcbf5991c

Observation edae7a6e-862e-403d-9f69-66a3ca59ff26 · outbound

This paper cites Dabney, G.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Dabney, G

Reference 14

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source=pdf_text observed=2026-08-03T05:00:40.950310Z digest=sha256:af5267eb5c9a9cd9176951d85d22454db725bf2113bf8c9ee7b4a4adbe71789b

Observation 00909810-6c3e-4649-95b5-985349f0d1c9 · outbound

This paper cites Dabney, M.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Dabney, M

Reference 15

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source=pdf_text observed=2026-08-03T05:00:41.008319Z digest=sha256:3f0942de45a3faed3d3e15a5502e00db44fcbd1dd0262739fddd1a1b6f7d09e1

Observation 74d39c56-2a3a-4ab3-865e-a73df8ab0440 · outbound

This paper cites Eysenbach, X.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Eysenbach, X

Reference 16

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source=pdf_text observed=2026-08-03T05:00:41.059367Z digest=sha256:d38dfa1ac397d3a9fc21eb0573d55dbc58210000d6a40d58cb5553b4ca98272d

Observation bb1614d3-c3a0-42db-8970-e075bf392d5a · outbound

This paper cites On the Fundamental Limitations of Dual Static CVaR Decompositions in Markov Decision Processes.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity On the Fundamental Limitations of Dual Static CVaR Decompositions in Markov Decision Processes

Reference 17

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source=pdf_text observed=2026-08-03T05:00:41.104568Z digest=sha256:45f06c4adfad3a06991e49592062540e215ec7209b94b2e570671a5ca71a5b73

Observation f2d254f4-aba0-49c7-8846-0f41a3798df8 · outbound

This paper cites Greenberg, Y.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Greenberg, Y

Reference 18

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source=pdf_text observed=2026-08-03T05:00:41.176033Z digest=sha256:aa97c8178fc35d04b40cf5a4f89d24c5972d534af3d94f81256b829aec82223d

Observation 0c36b96f-f091-4f3f-aefe-0cd730cccb2c · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-03T05:00:41.237882Z digest=sha256:3cf40bd304a72126d76947b887d3e8d42d7c42d49e19710171c84136e048b5b0

Observation a4137331-f899-40a4-8544-fd419f5f7bbf · outbound

This paper cites Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Q-learning for Quantile MDPs: A Decomposition, Performance, and Convergence Analysis

Reference 20

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source=pdf_text observed=2026-08-03T05:00:41.317966Z digest=sha256:54b616bf076b14ee97868f95256e9d0039d07f70b77a44c5f5313ccb6be20d7b

Observation eaf31ef1-97c3-4fbe-ac67-78d94a7bb68c · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 21

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source=pdf_text observed=2026-08-03T05:00:41.367988Z digest=sha256:c06d4de50f867647b5a152f22690075ba8f0d279ab2ae47912ee7fd8245d26fe

Observation d201daf5-b84a-4e9b-8b43-62e41aa8270a · outbound

This paper cites Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning

Reference 22

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source=pdf_text observed=2026-08-03T05:00:41.438755Z digest=sha256:cf9b9073764790fa56e07cfb72e3ce421f753533c3c78dea1dc1890efbab4f76

Observation e340c233-7c78-4da5-b08b-61afbb6089f9 · outbound

This paper cites Keramati, C.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Keramati, C

Reference 23

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source=pdf_text observed=2026-08-03T05:00:41.572723Z digest=sha256:b34bac95203c6db0d281be233182230a57f68d25108ade187d55ff6ca63407dc

Observation ae9fe827-eee9-466a-9bca-194baaeb0221 · outbound

This paper cites Kim and S.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Kim and S

Reference 24

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source=pdf_text observed=2026-08-03T05:00:41.681722Z digest=sha256:aa232f20636a40368d77e2c59289b30016faf9b9617372c11f221494526ae212

Observation 6e81dad5-dfae-458f-8898-9bdaa125f673 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-03T05:00:41.825187Z digest=sha256:104736f378e2100e6ae4936987f9a9c55e9c1a046f4268c9aaec3a4f14306df7

Observation d092259a-3035-49a5-9b4b-246cc0652de6 · outbound

This paper cites Majumdar and M.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Majumdar and M

Reference 26

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source=pdf_text observed=2026-08-03T05:00:41.937723Z digest=sha256:aebb0779bfaacadec2ce65ac4c33cefb82f69f88ae7abca233c10186da7e7da0

Observation 729129bc-3353-48b3-833d-1f61bc861859 · outbound

This paper cites Return Capping: Sample-Efficient CVaR Policy Gradient Optimisation.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Return Capping: Sample-Efficient CVaR Policy Gradient Optimisation

Reference 27

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Observation be61549a-1cab-4545-831e-d51f53e378f7 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-03T05:00:42.251825Z digest=sha256:212b05bbdbea68557774ec9171ff4c2a7a612ad708460e832a4786c5d0039a2c

Observation cf48ee31-9f0b-4ac6-a472-356438d6d49f · outbound

This paper cites Moghimi and H.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Moghimi and H

Reference 29

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source=pdf_text observed=2026-08-03T05:00:42.378177Z digest=sha256:9816f29e63fcf4c297880fe392983816879c71e990145a5ba7a50ff3174c1ecd

Observation 7438794a-7c70-4749-a508-ff7d7a7d20c5 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 30

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source=pdf_text observed=2026-08-03T05:00:42.490132Z digest=sha256:2ee1e8878f02bd2b0b32038d37125ca4d2636b1d2bcf55dae3ed150e440fc70a

Observation f5d769e9-c29d-47b9-b07d-5c4ecd168d1e · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 31

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source=pdf_text observed=2026-08-03T05:00:42.614452Z digest=sha256:babe75956064d22244d7bdc122ffbb3491bf3f35ada68440cabd2b011d553a65

Observation 62ec911d-9c58-48b3-ab5a-7da5ae4120e1 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-03T05:00:42.726586Z digest=sha256:1530c183ec3f213057ec960b82066d9aa8e9c5a81df66a5a121f24ef825bebbd

Observation b211e744-065c-4019-a2ea-774e7c3d15be · outbound

This paper cites A Survey of Temporal Credit Assignment in Deep Reinforcement Learning.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity A Survey of Temporal Credit Assignment in Deep Reinforcement Learning

Reference 33

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source=pdf_text observed=2026-08-03T05:00:42.882135Z digest=sha256:ca9b9246fcef2fd4519b4b01dbe304ef9c78a9e2758c8c87a8489617613d205f

Observation 2e2115d2-677e-4695-ad35-38fcc05b500f · outbound

This paper cites Optimizing Return Distributions with Distributional Dynamic Programming.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Optimizing Return Distributions with Distributional Dynamic Programming

Reference 34

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source=pdf_text observed=2026-08-03T05:00:43.012228Z digest=sha256:3222542f95bd310668278abe0b1c76fa9de576bc17fb2367801d277309f80802

Observation 1a773011-ce78-4120-9009-285824cd6501 · outbound

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Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 35

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source=pdf_text observed=2026-08-03T05:00:43.149409Z digest=sha256:0a73f0b0cfb8d272b230b05a1cb574f7240fd07f82aebd2852652f986e36450e

Observation 53326bf2-181c-449b-8977-47bad8926ed5 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 36

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source=pdf_text observed=2026-08-03T05:00:43.264614Z digest=sha256:12d7a84931e851a8203fc6e5248f6a5bc56122aac3a05fbe0e9e401ea09fa1b6

Observation 92fddbf0-801c-47e2-80b6-a4a83f2f405d · outbound

This paper cites Ruszczy´ nski.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Ruszczy´ nski

Reference 37

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source=pdf_text observed=2026-08-03T05:00:43.360117Z digest=sha256:950e4a189e9ac428cdd190f6806c8b8a3007097ba9b567a45115ded83528a5b0

Observation b35cd1bb-042c-4579-839e-eaac1788beeb · outbound

This paper cites Schneider, J.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Schneider, J

Reference 38

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source=pdf_text observed=2026-08-03T05:00:43.482599Z digest=sha256:abd5c8240c0360fe15aba7b5c8790844e1893a9150c15355503a9ac470e6e99b

Observation 616e5455-4612-411f-8d36-fd4791f14257 · outbound

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Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 39

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source=pdf_text observed=2026-08-03T05:00:43.594072Z digest=sha256:a5e984a2cdf7d44bcf5938713162e0ad96f3b13d00840592e1a130c175e257d3

Observation 3f86a70a-847f-41be-b1fa-212e1e91e867 · outbound

This paper cites Stanko and K.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Stanko and K

Reference 40

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no resolver link, observed 2026-08-03T05:00:43.714533Z

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source=pdf_text observed=2026-08-03T05:00:43.714533Z digest=sha256:f5755e6b50d5c625dbb1bbee5479cd7bdb2ec028e74ece16de235a33a4411663

Observation cf626c4b-2321-4e4f-9ad4-219184d8c17f · outbound

This paper cites Tamar, Y.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Tamar, Y

Reference 41

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source=pdf_text observed=2026-08-03T05:00:43.837265Z digest=sha256:c7498c1862f63e43a49882b0aa72e98b3a7b44a1cc9844b744eccec1765221b7

Observation 48d6a032-460d-4725-afe5-65b541d9ceab · outbound

This paper cites Tamar, Y.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Tamar, Y

Reference 42

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source=pdf_text observed=2026-08-03T05:00:43.927821Z digest=sha256:21a406edc4aed2f5385014dab6dfcc16416a00dfc4f9faee3dac1a5197e64baa

Observation b54b3462-8402-4d70-9759-9acf20d60574 · outbound

This paper cites Worst Cases Policy Gradients.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Worst Cases Policy Gradients

Reference 43

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source=pdf_text observed=2026-08-03T05:00:44.013222Z digest=sha256:2ef2a7d3614839acfe883e4c8f45d3b88badff15f988b3d393aac4e88734e9ec

Observation 4e6d8b5c-516a-49dc-9234-fcf3b0c2b91c · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 44

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source=pdf_text observed=2026-08-03T05:00:44.133408Z digest=sha256:dd42017bd472fd801d68719b40155168079eeee5fd7576b50c018374fda6f72b

Observation de8b305c-6488-46cd-9ff0-292661dde551 · outbound

This paper cites an unresolved cited work.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Unresolved cited work

Reference 45

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source=pdf_text observed=2026-08-03T05:00:44.246938Z digest=sha256:fca4ca98dcb8b8f5f49daea15dcf0ed5c98ecfcfb1625ac6e47b419f07a5be45

Observation 9c91a862-2c0c-4c93-b634-0fdaf4ed1ae8 · outbound

This paper cites A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents

Reference 46

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source=pdf_text observed=2026-08-03T05:00:44.339758Z digest=sha256:b9ba837c3fc19c0dc5bcf8d849b4de6325fcdb9f72270f72990e6d2d3064c92e

Observation c15afc32-40a2-4253-ad09-b658561e007a · outbound

This paper cites Wang and M.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity Wang and M

Reference 47

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source=pdf_text observed=2026-08-03T05:00:44.406778Z digest=sha256:e77955234a716a2ecabae0f926db77c4953917f5b23b78c62ab7ef469c851072

Observation d82bf449-a6d3-4b21-891b-2cf4bc7cd561 · outbound

This paper cites − 0−1X t=0 γtr(st, at) +z ! − +z − # =−z − +z − = ˆv† 0(s, z). 29 We follow with atk+ 1: ˆv† k+1(s, z) =E τ∼P ¯π(·,z∗ l ) s.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity − 0−1X t=0 γtr(st, at) +z ! − +z − # =−z − +z − = ˆv† 0(s, z). 29 We follow with atk+ 1: ˆv† k+1(s, z) =E τ∼P ¯π(·,z∗ l ) s

Reference 48

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no resolver link, observed 2026-08-03T05:00:44.506107Z

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source=pdf_text observed=2026-08-03T05:00:44.506107Z digest=sha256:8d15640cf26fec4fff6c01a682a9f413a71855582c985d19af50cf7edd9ffb6d

Observation 864970d3-76df-4999-b090-f065ae9aaa12 · outbound

This paper cites These are used to calculate the empirical return distribution, the empirical CVaR performance as well as analyzing the number of times the robot enters the crater per episode.

Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity These are used to calculate the empirical return distribution, the empirical CVaR performance as well as analyzing the number of times the robot enters the crater per episode

Reference 49

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source=pdf_text observed=2026-08-03T05:00:44.567451Z digest=sha256:180b3899ad497e4741d6ff1c47b3cd3aab79ff0aeafde812878943ce0f90caed

Pith citing papers

Observation 19a246b1-bc52-435f-aa88-b39ecccd7936 · inbound

Sample Complexity for Markov Decision Processes and Stochastic Optimal Control with Static Risk Measures cites this paper.

Sample Complexity for Markov Decision Processes and Stochastic Optimal Control with Static Risk Measures Reward Redistribution for CVaR MDPs using a Bellman Operator on L-infinity

Reference 18

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arxiv_id, observed 2026-07-01T02:17:19.184541Z

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source=pdf_text observed=2026-05-10T19:31:33.732451Z digest=sha256:68391bde53c3fdecf8a1ef7ffd0bb481a4a9d29015d1e211b0c4c360ae8a59f2