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Paper Citation Record · LEDGER

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

As of 20 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 2026-08-20T06:33:59.587034+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:e19609163373efed40de3fbfa300b0707c1c9bc338b92a03194f6ecc6bcde6c4

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:d00d7948457ff4a0c089a26e4f12da3c9a8c7ddcc87c807ab3141e3e2e9c1158

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:fae8d9b0ee166bb0877a482b8547267f372401785f825e364f64bb22bf6955c1

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=sha256:5c3c5f2ccbf9a1ec01fecb668c7e96c2d2dd4f032683a55efe7e1684adfb5406

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=sha256:256badf0135d064a683752f5e4585ef44eaa10d51b12c35025e3c0778b338b25

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=sha256:5a7ceb3cec97f02de31eadc5b5d4e6d6b9e77bc64218d1299521dbb4af643168

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=sha256:7be7be59eb4d7fef245f970562aacab9b587145d57415bc1b84e0974b6645ac8

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:f6148b69a69bde637c43b36264b8bef3b66f9e2214926dc52fcc11797d431b82

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:aec038ec8d4264964f7692ac7146e0e39dc028da3d4fee816ef0a76a86141154

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=sha256:431670fa6396e138f8f6cb647dd993cd0ca4c27e9f5148bc8b33edda2df75215

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=sha256:777154396fb90b34146ac8737de5d392a443ec0b7ba07598a935d0bc13f42bac

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:a76cefee3b8205dcaa52581fe27e485cf5412025ebb7314affa6a69a3c33b531

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=sha256:42dd3078a52dc7b76074ec04e481c040f351c64faf1e7191c6ddd5475c847824

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:d943fcd608e5dcdf5d1018d30b28e0cb7dfaeb7a60f0c98a87a8151e1f22ca0b

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=sha256:7f4cdb37187a62403f4d51f0d93bb6f062650ef4d6796bf7c8a85981e112cd1c

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:ffc2cfba1165c6ac98b0e7ca0b159caac087b138ed1092677be2b99ae28f982e

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=sha256:6b7e59aad21ed82e18fd73d3bdf9c62ded577b81ef64535da4657893eca527fb

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=sha256:62ac9048825f0c7bae686c47abeac0064fcf3cf2d665880c20e01af03dd3101b

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:e32fcd8663c534deaf59cd7af3daa978c613b6884c58eb7d74f47808abac9a6c

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=sha256:22b0385c0605d3dcab9dd8e0b7d50df62ff681519a82f473df2c75c8a2704521

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:a2785b4bd627e2c96c16858f8eb1abe3231eb573a14d85900b6bab1b309657a7

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=sha256:45e6a7250380a4718cedab69018747af6285e26f1ec1d9593b9307dc3ec9d0b2

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=sha256:880ed9eecf611ad204c058f814a666e1c57d38f8ccafde6cf8e406fa8ee7aede

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=sha256:3c681394bfe28741bee8a36003e39f19f17e54cb4a63fef476128e2ee6b59240

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:b8e614a2d7fa13294226dfd2c3a7d4cf250cbf247abeb5c0abc98553c310af69

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=sha256:1d7c5b24ca5fc5f4f76379145c815f663b3515e5c77d7aa28b3b4e012b9a779a

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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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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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=sha256:6047c711191656a2f3102e21ffcb9d1f5e1a71087b71e451724350aae3600c2d

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:aa1d917b21ac3211e652b0aaadcaeb14e35c5c3290c5667b14dbad76d7a09c8f

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:b4b0d1dca954317d539ce307981650a50d5b6190db4bf4fb42c9f76905419d2b

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=sha256:65b417bd5a18ea932dea6869a103db3e9f674b7cf16a282df83da3c8a9a9a854

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=sha256:8cd5b5253d0cec6133844a2dda1fa7c0edf70e82789266101c0456ccc003766f

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=sha256:2beed7405c871d27914fba461c40b0b7bcfcf9233939df01919417ffb29b4b9e

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=sha256:91a20329abac89e7a050defcb4922165a7064a9978b978012a39593afb165882

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:eaaa3296a0da23fc71990f8eebe91689ce60e3979d3e7a95e46f383d88c590d7

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=sha256:28781108608ce0c7f9e122811c25fad0932c549c4400d6e4b462c5a49f5605a9

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

This paper cites an unresolved cited work.

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=sha256:56a6b55c3e90fb8b4fbf0e8d383fc6bd83f358a4d88032792d2cbc44359ef1b6

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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source=pdf_text observed=2026-08-03T05:00:43.714533Z digest=sha256:ebd9a0f0a3070e9a940910bd1cc6b8cc41c42c6a86d1998ca515396ce4d5b5b7

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=sha256:561580431f0c1fd4f955df197cad5321301e0c5434ba6373c7b6414c045248d4

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:b3ae10904f4a1483ce8f08fdb1e942b80da7201a68390ea2b173e2fc8f4a87e0

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=sha256:78ac5ef42966070c1d073e6b6e27ed102c14e29f48d8ed34a37107634479840a

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=sha256:67f25279212c102132fcd3df70cc4707b6998f8e0488805fd8752bc438ca957a

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=sha256:3d11c0e37e6db03712358c10adb3a03533f3e756d3af9ab752f45caff10635d3

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:d6fceb5415bcc8aed5c50b946e6025a554788a3ae6f7ab6f8aca4b829d1699e1

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=sha256:6d6beea660c40d28309b56d5b8232621dd47f25443e9d1fe658a7bd9fce0c87e

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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source=pdf_text observed=2026-08-03T05:00:44.506107Z digest=sha256:ff8c42bcc37fef068601226d6e2dc1dece40f3309b687dbf09d560b14caf413c

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=sha256:19727cb5fc9fd3b0b1d0b7e3d19948924a646e8a387dac307a6d3d724e89a4ae

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=sha256:90db2c2d5978e3a7f6cfad64188a1703d7ffcfd27ed2b30f6182bd8353aea175