Paper Citation Record · LEDGER

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes

As of 17 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 1 inbound Pith citation observation for arXiv:2502.09432.

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

pith.paper-citation-record.v1
2502.09432 v1

Coverage vector

measured 57 of 57 reference resolution

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

57 of 57 outbound references displayed

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External citation measurements

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Outbound references

Observation 0b6c4991-7123-41f6-87a7-945dd0b2482a · outbound

This paper cites Tsitsiklis.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Tsitsiklis

Reference 1

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Observation d068d777-fdf7-4f58-bc22-82cf9e89f98e · outbound

This paper cites Robust data-driven dynamic programming.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust data-driven dynamic programming

Reference 2

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Observation aa9b5782-8f78-4873-bde4-cda8b7a91372 · outbound

This paper cites Scaling up robust mdps using function approxi- mation.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Scaling up robust mdps using function approxi- mation

Reference 3

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This paper cites Robust control of markov decision processes with uncertain transition matrices.Oper.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust control of markov decision processes with uncertain transition matrices.Oper

Reference 4

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Reference 5

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Observation 419da8df-17b9-43d8-a4fb-fb994e518124 · outbound

This paper cites Robustness and generalization, 2010.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robustness and generalization, 2010

Reference 6

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This paper cites Hospedales.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Hospedales

Reference 7

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Observation 5b6896b6-866b-41e5-9487-998733ad90b7 · outbound

This paper cites Assessing generalization in deep reinforcement learning, 2018.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Assessing generalization in deep reinforcement learning, 2018

Reference 8

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Observation 5775abf2-2ba1-44f5-9c20-2c4a0fda77f2 · outbound

This paper cites Robust markov decision processes.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust markov decision processes

Reference 9

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Observation faf38675-618d-4f52-be99-3259c365fd6e · outbound

This paper cites Robust mdps with k-rectangular uncertainty.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust mdps with k-rectangular uncertainty

Reference 10

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Observation 6958771c-17eb-476e-969f-82f69e30975c · outbound

This paper cites Robust markov decision process: Beyond rectan- gularity, 2018.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust markov decision process: Beyond rectan- gularity, 2018

Reference 11

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Observation 50b4c15e-7a13-4973-ab19-404a9d6c2dc2 · outbound

This paper cites Kaufman and Andrew J.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Kaufman and Andrew J

Reference 12

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This paper cites Andrew Bagnell, Andrew Y.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Andrew Bagnell, Andrew Y

Reference 13

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Observation bf527111-eaf5-481b-b603-8ffde6c430e2 · outbound

This paper cites Partial policy iteration for l1-robust markov decision processes, 2020.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Partial policy iteration for l1-robust markov decision processes, 2020

Reference 14

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Observation dcd86abc-f994-4f57-93c5-48c9c9c0cfb2 · outbound

This paper cites Online robust reinforcement learning with model uncertainty, 2021.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Online robust reinforcement learning with model uncertainty, 2021

Reference 15

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Observation 6841709c-70a0-49ff-950e-7ce3ca8ea7ed · outbound

This paper cites Policy gradient method for robust reinforcement learning, 2022.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Policy gradient method for robust reinforcement learning, 2022

Reference 16

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This paper cites Policy gradient in robust mdps with global convergence guarantee, 2023.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Policy gradient in robust mdps with global convergence guarantee, 2023

Reference 17

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Observation 6066d4e6-4f32-416a-b875-dc1bf49c8064 · outbound

This paper cites Twice regularized mdps and the equivalence between robustness and regularization, 2021.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Twice regularized mdps and the equivalence between robustness and regularization, 2021

Reference 18

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Observation b1e7768d-3351-4017-9ac6-fb82a947672d · outbound

This paper cites Efficient value iteration for s-rectangular robust markov decision processes.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Efficient value iteration for s-rectangular robust markov decision processes

Reference 19

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Observation 2fca1ffd-6e9d-4eda-96ab-fcf794ce255d · outbound

This paper cites Pol- icy gradient for rectangular robust markov decision processes.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Pol- icy gradient for rectangular robust markov decision processes

Reference 20

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Observation 580cf6d2-91f7-4995-a432-781b475e0600 · outbound

This paper cites Natural actor-critic for robust reinforcement learning with function approximation.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Natural actor-critic for robust reinforcement learning with function approximation

Reference 21

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Observation 9f7ec817-9d0e-4894-bcf8-b6677202d6d0 · outbound

This paper cites Robust reinforce- ment learning via adversarial kernel approximation, 2023.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust reinforce- ment learning via adversarial kernel approximation, 2023

Reference 22

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Observation ddc55e57-2f07-4962-95fa-100a13f7354c · outbound

This paper cites Solving non-rectangular reward-robust mdps via frequency regularization, 2023.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Solving non-rectangular reward-robust mdps via frequency regularization, 2023

Reference 23

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This paper cites Smith and Mavina K.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Smith and Mavina K

Reference 24

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Observation fc0ad112-f3c5-4d6d-a40c-cb072c396f7f · outbound

This paper cites Puterman.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Puterman

Reference 25

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This paper cites Tractable robust markov decision processes, 2024.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Tractable robust markov decision processes, 2024

Reference 26

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This paper cites Sutton and Andrew G.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Sutton and Andrew G

Reference 27

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This paper cites Wasserstein robust reinforcement learning, 2019.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Wasserstein robust reinforcement learning, 2019

Reference 28

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Observation aaba2e2f-1859-4405-9b5d-cf5a4484971a · outbound

This paper cites Robust $\phi$-divergence MDPs.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust $\phi$-divergence MDPs

Reference 29

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Reference 30

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This paper cites Bellemare.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Bellemare

Reference 31

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This paper cites The geometry of robust value functions.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes The geometry of robust value functions

Reference 32

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Observation c2934878-e35f-4b07-b3aa-3d54fe13f949 · outbound

This paper cites Lightning Does Not Strike Twice: Robust MDPs with Coupled Uncertainty.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Lightning Does Not Strike Twice: Robust MDPs with Coupled Uncertainty

Reference 33

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Reference 34

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This paper cites Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, EvgeniBurovski, PearuPeterson, WarrenWeckesser, JonathanBright, StéfanJ.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, EvgeniBurovski, PearuPeterson, WarrenWeckesser, JonathanBright, StéfanJ

Reference 35

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Observation 649bac79-e0ab-4eff-af3e-0a715a06007b · outbound

This paper cites Policy gradient methods for reinforcement learning with function approximation.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Policy gradient methods for reinforcement learning with function approximation

Reference 36

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Reference 37

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This paper cites Cambridge University Press, March 2004.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Cambridge University Press, March 2004

Reference 38

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This paper cites Policy gradient for reinforce- ment learning with general utilities, 2023.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Policy gradient for reinforce- ment learning with general utilities, 2023

Reference 39

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This paper cites This makes sense, as the more the agent visits states with high uncertainty, the higher is the ability of the adversary to undermine it.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes This makes sense, as the more the agent visits states with high uncertainty, the higher is the ability of the adversary to undermine it

Reference 40

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This paper cites nominal value functionvπ R).

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes nominal value functionvπ R)

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:36:19.880758Z

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This paper cites This can be done, by putting negative entries ofk at maximal entries of vπ β, and positive entries ofkT at states which has minimum uncertainty value function.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes This can be done, by putting negative entries ofk at maximal entries of vπ β, and positive entries ofkT at states which has minimum uncertainty value function

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:36:19.870305Z

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Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 44

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Reference 45

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Observation 2edeacfe-e812-409b-92de-aaa3a4193d7d · outbound

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Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 46

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Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 47

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Observation 6083aa55-ce62-4c26-95b0-2ae338ed70ce · outbound

This paper cites Robust policy evaluation is proven to be NP-hard for general uncertainty sets defined as intersections of finite hyperplanes [9].

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Robust policy evaluation is proven to be NP-hard for general uncertainty sets defined as intersections of finite hyperplanes [9]

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:36:19.806953Z

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Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 49

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Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 50

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Observation 30afade0-ed22-44d1-97b1-8630032d946e · outbound

This paper cites This method is simple to implement but computationally expensive, as it evaluatesA for a large number of randomly generated vectors.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes This method is simple to implement but computationally expensive, as it evaluatesA for a large number of randomly generated vectors

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:36:19.774632Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c2615a3f-5157-4667-a01d-4b66477e2297 · outbound

This paper cites an unresolved cited work.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:36:19.762906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1f70338b-74cb-460f-8826-c216989c711e · outbound

This paper cites an unresolved cited work.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:36:19.750523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68957e29-950d-41b5-8977-65ddcfb75bb0 · outbound

This paper cites This method provides the exact solution but is computationally more expensive than the spectral method.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes This method provides the exact solution but is computationally more expensive than the spectral method

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:36:19.739160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 78aee9ed-86aa-46ea-97d7-7c98b435ce26 · outbound

This paper cites an unresolved cited work.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:36:19.727520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9235abd9-1024-4bd0-b9ab-3a162974a240 · outbound

This paper cites an unresolved cited work.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-07T21:36:19.716000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a0231bc6-ba6b-48ac-9920-1d824e750f52 · outbound

This paper cites The results, including the optimal values and computational times, are recorded for each method.

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes The results, including the optimal values and computational times, are recorded for each method

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T21:36:19.705050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Pith citing papers

Observation 233a9c31-c3aa-46fd-b70b-debdf5215a43 · inbound

Robust Markov Decision Processes on Continuous State Spaces cites this paper.

Robust Markov Decision Processes on Continuous State Spaces Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-29T10:33:18.781161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.