Provable Partially Observable Reinforcement Learning with Privileged Information | Paper Citation Record

Observation e7163470-73cd-472d-b4a6-f1ebc205c09e · outbound

This paper cites End-to-end training of deep visuomotor policies.

Provable Partially Observable Reinforcement Learning with Privileged Information End-to-end training of deep visuomotor policies

Reference 1

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Observation 5cbeeea6-e844-492d-99e6-5820f41ad289 · outbound

This paper cites Learning dex- terous in-hand manipulation.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning dex- terous in-hand manipulation

Reference 2

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Observation 1dd38f47-686d-40a7-a6b4-632b05f0de02 · outbound

This paper cites Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving.

Provable Partially Observable Reinforcement Learning with Privileged Information Safe, Multi-Agent, Reinforcement Learning for Autonomous Driving

Reference 3

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Observation ea9f9c37-b818-4012-99d4-d365c7d89a29 · outbound

This paper cites Deep reinforcement learning for autonomous driving: A survey.

Provable Partially Observable Reinforcement Learning with Privileged Information Deep reinforcement learning for autonomous driving: A survey

Reference 4

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Observation 6cd51fa3-3e5b-4ea3-b2a2-72417c621d80 · outbound

This paper cites Pomdp-based statistical spoken dialog systems: A review.

Provable Partially Observable Reinforcement Learning with Privileged Information Pomdp-based statistical spoken dialog systems: A review

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.396226Z

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Observation c90bb442-a7bd-4b7e-8cb8-45907d5e3881 · outbound

This paper cites Informing sequential clinical decision-making through reinforcement learning: an empirical study.

Provable Partially Observable Reinforcement Learning with Privileged Information Informing sequential clinical decision-making through reinforcement learning: an empirical study

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.400361Z

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Observation a70d1743-7a2a-4167-b3e5-3c6ae7eb9f07 · outbound

This paper cites The complexity of markov decision processes.

Provable Partially Observable Reinforcement Learning with Privileged Information The complexity of markov decision processes

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.404638Z

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Observation 23b1aab0-39eb-4063-bc2a-0f7b5c539fe7 · outbound

This paper cites Pac reinforcement learning with rich observations.

Provable Partially Observable Reinforcement Learning with Privileged Information Pac reinforcement learning with rich observations

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.408509Z

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Observation 6edf07d0-4530-4dc5-9c96-d945087cfccc · outbound

This paper cites Sample-e fficient reinforce- ment learning of undercomplete POMDPs.

Provable Partially Observable Reinforcement Learning with Privileged Information Sample-e fficient reinforce- ment learning of undercomplete POMDPs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.412288Z

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Observation 35341c44-0538-44a0-ad0d-25693ee815aa · outbound

This paper cites A counterexample in stochastic optimum control.

Provable Partially Observable Reinforcement Learning with Privileged Information A counterexample in stochastic optimum control

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.416105Z

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Observation 85cdf6c5-84e0-402f-add6-a0d965b262bd · outbound

This paper cites On the complexity of decentralized decision making and detection problems.

Provable Partially Observable Reinforcement Learning with Privileged Information On the complexity of decentralized decision making and detection problems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.419988Z

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Observation 0e9392e0-05ed-48ab-a20b-8989b49afb6f · outbound

This paper cites Multi- agent actor-critic for mixed cooperative-competitive environments.Advances in Neural Informa- tion Processing Systems, 30, 2017.

Provable Partially Observable Reinforcement Learning with Privileged Information Multi- agent actor-critic for mixed cooperative-competitive environments.Advances in Neural Informa- tion Processing Systems, 30, 2017

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.424233Z

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Observation 4f837fb5-a935-4d6e-b68f-d7ec928e50b6 · outbound

This paper cites QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information QMIX: Monotonic value function factorisation for deep multi-agent reinforcement learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.428099Z

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Observation 0b6db165-42da-4fcc-b2dc-b38653b2e6c9 · outbound

This paper cites Counterfactual multi-agent policy gradients.

Provable Partially Observable Reinforcement Learning with Privileged Information Counterfactual multi-agent policy gradients

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.431857Z

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Observation 4ae1370d-cfe2-4e80-9d80-3e49b8411cd9 · outbound

This paper cites Grandmas- ter level in StarCraft II using multi-agent reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Grandmas- ter level in StarCraft II using multi-agent reinforcement learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.435449Z

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Observation 209f5775-dff3-4ee1-8fbc-63ef7fd0f64c · outbound

This paper cites Learning quadrupedal locomotion over challenging terrain.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning quadrupedal locomotion over challenging terrain

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.439379Z

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Observation b086a5a3-43c3-4730-9c9c-83b87f90fc3f · outbound

This paper cites Learning robust perceptive locomotion for quadrupedal robots in the wild.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning robust perceptive locomotion for quadrupedal robots in the wild

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.877864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72e2ad17-e185-48ce-962d-7f900b515742 · outbound

This paper cites Learning by cheating.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning by cheating

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.865509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f8827aa1-a12f-4b16-b09e-b5af8efc6b35 · outbound

This paper cites Asymmetric actor critic for image-based robot learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Asymmetric actor critic for image-based robot learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.853512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3dbd4a4d-4b10-4558-9917-3494ab24f717 · outbound

This paper cites Learning in pomdps is sample- efficient with hindsight observability.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning in pomdps is sample- efficient with hindsight observability

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.841243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4833688b-eb7c-41d0-a7a8-da1d7b233706 · outbound

This paper cites Sample- efficient learning of pomdps with multiple observations in hindsight.

Provable Partially Observable Reinforcement Learning with Privileged Information Sample- efficient learning of pomdps with multiple observations in hindsight

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.828703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation afb14ff5-9add-461f-830f-dd4432bae525 · outbound

This paper cites Learning in observable POMDPs, without computationally intractable oracles.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning in observable POMDPs, without computationally intractable oracles

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.815988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6b6818fe-b22c-491d-854c-f95eb52a8bed · outbound

This paper cites On oracle-e fficient pac rl with rich observations.

Provable Partially Observable Reinforcement Learning with Privileged Information On oracle-e fficient pac rl with rich observations

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.803818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 47c406f7-1a2d-4fae-afdd-5786d14ebff9 · outbound

This paper cites Provably e fficient rl with rich observations via latent state decoding.

Provable Partially Observable Reinforcement Learning with Privileged Information Provably e fficient rl with rich observations via latent state decoding

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.791388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cc6b3e90-541e-4674-8d86-9ce17c4e78f7 · outbound

This paper cites Kinematic state abstraction and provably efficient rich-observation reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Kinematic state abstraction and provably efficient rich-observation reinforcement learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.779272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 217b5634-c3f1-4990-989d-548706502368 · outbound

This paper cites Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Exploration is Harder than Prediction: Cryptographically Separating Reinforcement Learning from Supervised Learning

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-12T05:00:57.892712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d6220eb8-cd38-4b8b-b43c-fb142e56c383 · outbound

This paper cites Provable reinforce- ment learning with a short-term memory.

Provable Partially Observable Reinforcement Learning with Privileged Information Provable reinforce- ment learning with a short-term memory

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.766737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cd64147e-b6ea-4d4e-9728-8d54b405e90e · outbound

This paper cites When is partially observable rein- forcement learning not scary? In Conference on Learning Theory, pages 5175–5220, 2022.

Provable Partially Observable Reinforcement Learning with Privileged Information When is partially observable rein- forcement learning not scary? In Conference on Learning Theory, pages 5175–5220, 2022

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.754554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 737e6c1e-7190-412b-909f-d6d980fe8e94 · outbound

This paper cites Partially observable multi-agent RL with (quasi-)e fficiency: the blessing of information sharing.

Provable Partially Observable Reinforcement Learning with Privileged Information Partially observable multi-agent RL with (quasi-)e fficiency: the blessing of information sharing

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.742068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c383ef95-b6ce-471b-b251-94451ae6aab7 · outbound

This paper cites Schapire.

Provable Partially Observable Reinforcement Learning with Privileged Information Schapire

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.729516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 48aa0392-b631-4fd2-89ff-f49f5db7b751 · outbound

This paper cites Represent to control partially ob- served systems: Representation learning with provable sample efficiency.

Provable Partially Observable Reinforcement Learning with Privileged Information Represent to control partially ob- served systems: Representation learning with provable sample efficiency

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.717368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e2754bc8-d010-4a96-be31-39ae8a9d93a3 · outbound

This paper cites Partially observable RL with b-stability: Unified structural condition and sharp sample-e fficient algorithms.

Provable Partially Observable Reinforcement Learning with Privileged Information Partially observable RL with b-stability: Unified structural condition and sharp sample-e fficient algorithms

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.705076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af9dad91-3fc7-48d2-89f3-f5753195c22f · outbound

This paper cites Reinforcement learning from partial observation: Linear function approximation with provable sample e fficiency.

Provable Partially Observable Reinforcement Learning with Privileged Information Reinforcement learning from partial observation: Linear function approximation with provable sample e fficiency

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.692309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b66ce82c-c450-40e6-93c4-2050fb6e6a4f · outbound

This paper cites Pessimism in the face of confounders: Provably efficient offline reinforcement learning in partially observable markov decision pro- cesses.

Provable Partially Observable Reinforcement Learning with Privileged Information Pessimism in the face of confounders: Provably efficient offline reinforcement learning in partially observable markov decision pro- cesses

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.679947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation aec8ff2d-a16a-497f-9e24-2e5ac3d3718c · outbound

This paper cites Optimistic MLE: A generic model-based algorithm for partially observable sequential decision making.

Provable Partially Observable Reinforcement Learning with Privileged Information Optimistic MLE: A generic model-based algorithm for partially observable sequential decision making

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.667308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 86df68e4-ed4d-4a4f-8aa1-6c371f8fe8fd · outbound

This paper cites an unresolved cited work.

Provable Partially Observable Reinforcement Learning with Privileged Information Unresolved cited work

Reference 36

Resolution: unresolved; raw_fallback, observed 2026-08-12T05:00:58.655043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 72599437-b993-4eb5-a50e-1f38ec65ac56 · outbound

This paper cites Partially observable multi-agent reinforcement learning with information sharing, 2024.

Provable Partially Observable Reinforcement Learning with Privileged Information Partially observable multi-agent reinforcement learning with information sharing, 2024

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.642424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 105fcce5-289a-46c5-bcf2-969200142602 · outbound

This paper cites Planning in Observable POMDPs in Quasipolynomial Time.

Provable Partially Observable Reinforcement Learning with Privileged Information Planning in Observable POMDPs in Quasipolynomial Time

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.525271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cb4df1d-8d25-4114-9ec0-02605981450a · outbound

This paper cites Planning and learning in partially observ- able systems via filter stability.

Provable Partially Observable Reinforcement Learning with Privileged Information Planning and learning in partially observ- able systems via filter stability

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.629812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4b795815-13fc-490f-a582-00a8188a81bd · outbound

This paper cites Theoretical hardness and tractability of pomdps in rl with partial online state information, 2024.

Provable Partially Observable Reinforcement Learning with Privileged Information Theoretical hardness and tractability of pomdps in rl with partial online state information, 2024

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.617712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 311d25fe-b0d2-4841-a9de-df18d7812141 · outbound

This paper cites Leveraging fully observable policies for learning under partial observability.

Provable Partially Observable Reinforcement Learning with Privileged Information Leveraging fully observable policies for learning under partial observability

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.605312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8343e49c-fd3a-448d-994e-3cd4802dda99 · outbound

This paper cites Learning to jump from pixels.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning to jump from pixels

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.593020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation dca28fe8-bbb3-4f3e-9302-f672302aeb71 · outbound

This paper cites Tgrl: An algorithm for teacher guided reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Tgrl: An algorithm for teacher guided reinforcement learning

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.580773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 27473edb-659a-4496-8580-a62aae1ad57c · outbound

This paper cites Asymmetric DQN for partially observable reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Asymmetric DQN for partially observable reinforcement learning

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.568365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 73818330-0008-423b-82cd-5428279c758f · outbound

This paper cites Perfectdou: Dominating doudizhu with perfect information distillation.Advances in Neural Information Processing Systems, 35:34954–34965, 2022.

Provable Partially Observable Reinforcement Learning with Privileged Information Perfectdou: Dominating doudizhu with perfect information distillation.Advances in Neural Information Processing Systems, 35:34954–34965, 2022

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.556140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 86c05e3a-ba6c-4130-ad4c-fc2068feb608 · outbound

This paper cites Towards unifying behavioral and response diversity for open-ended learn- ing in zero-sum games.

Provable Partially Observable Reinforcement Learning with Privileged Information Towards unifying behavioral and response diversity for open-ended learn- ing in zero-sum games

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.544002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 46cfd868-9448-4408-8a6d-965ecd08c15e · outbound

This paper cites Unbiased asymmetric reinforcement learning under partial observability.

Provable Partially Observable Reinforcement Learning with Privileged Information Unbiased asymmetric reinforcement learning under partial observability

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.531166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d18c399a-2656-4fb1-9490-1eb289e362f7 · outbound

This paper cites A deeper understanding of state-based critics in multi-agent reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information A deeper understanding of state-based critics in multi-agent reinforcement learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.518806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 992bd910-ae36-4806-9b81-d38c65da0108 · outbound

This paper cites On cen- tralized critics in multi-agent reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information On cen- tralized critics in multi-agent reinforcement learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.506483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2e1a4770-5d02-4db9-b30e-1e7d478fe43c · outbound

This paper cites Learning belief representations for partially observable deep rl.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning belief representations for partially observable deep rl

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.493910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c202d67a-d224-46c0-8f92-717a8020d41d · outbound

This paper cites Learning belief representations for imitation learning in pomdps.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning belief representations for imitation learning in pomdps

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.481653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation bf86327d-f6bd-452b-95fd-7fd78af64a55 · outbound

This paper cites Belief-grounded networks for accelerated robot learning under partial observability.

Provable Partially Observable Reinforcement Learning with Privileged Information Belief-grounded networks for accelerated robot learning under partial observability

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.469046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1b8675e2-1378-493b-9b45-0aae522d1133 · outbound

This paper cites Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings.

Provable Partially Observable Reinforcement Learning with Privileged Information Learned Belief Search: Efficiently Improving Policies in Partially Observable Settings

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.583507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 892cabc8-9d4a-43ba-b625-39329c5c8d51 · outbound

This paper cites Flow-based recurrent belief state learning for pomdps.

Provable Partially Observable Reinforcement Learning with Privileged Information Flow-based recurrent belief state learning for pomdps

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.456809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4084d94e-4e65-4da7-8968-b4cec9add4ab · outbound

This paper cites Belief state actor-critic algorithm from separation principle for POMDP.

Provable Partially Observable Reinforcement Learning with Privileged Information Belief state actor-critic algorithm from separation principle for POMDP

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.444516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2882b484-5216-4df3-82a5-5405accbbe24 · outbound

This paper cites Neural belief states for partially observed domains.

Provable Partially Observable Reinforcement Learning with Privileged Information Neural belief states for partially observed domains

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.432094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6691a7d0-4711-4ad8-b0b7-68895a1f9f99 · outbound

This paper cites The wasserstein believer: Learning belief updates for partially observable environments through reliable latent space models.

Provable Partially Observable Reinforcement Learning with Privileged Information The wasserstein believer: Learning belief updates for partially observable environments through reliable latent space models

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.419475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 7f616ca9-4ad1-4b58-9440-50b8e78a14f2 · outbound

This paper cites Common informa- tion based markov perfect equilibria for stochastic games with asymmetric information: Finite games.

Provable Partially Observable Reinforcement Learning with Privileged Information Common informa- tion based markov perfect equilibria for stochastic games with asymmetric information: Finite games

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.313480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation af3b9a8a-b593-4bc1-812a-06b5c13054bd · outbound

This paper cites Decentralized stochastic con- trol with partial history sharing: A common information approach.

Provable Partially Observable Reinforcement Learning with Privileged Information Decentralized stochastic con- trol with partial history sharing: A common information approach

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.301288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cd4d198c-2a00-4d7f-a17b-ade838f12842 · outbound

This paper cites Sample-e fficient reinforcement learning of par- tially observable Markov games.

Provable Partially Observable Reinforcement Learning with Privileged Information Sample-e fficient reinforcement learning of par- tially observable Markov games

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.289167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4df6750a-8ad8-4153-98ff-fc5ce1da62c0 · outbound

This paper cites When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?.

Provable Partially Observable Reinforcement Learning with Privileged Information When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.614294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ec2666b-1ae8-49a4-bb75-441e8eb21da6 · outbound

This paper cites A sharp analysis of model-based reinforce- ment learning with self-play.

Provable Partially Observable Reinforcement Learning with Privileged Information A sharp analysis of model-based reinforce- ment learning with self-play

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.275849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 38b72e48-4179-4bd1-ad2b-17174936a734 · outbound

This paper cites V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL.

Provable Partially Observable Reinforcement Learning with Privileged Information V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.622093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2b1acf5-a996-4570-8c66-3f65afcea8f3 · outbound

This paper cites Algorithmic game theory.

Provable Partially Observable Reinforcement Learning with Privileged Information Algorithmic game theory

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.263260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 413df1b0-1e47-4182-8beb-ead88dbc369f · outbound

This paper cites Kakade, and Yishay Mansour.

Provable Partially Observable Reinforcement Learning with Privileged Information Kakade, and Yishay Mansour

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.251251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4a866159-e575-4a45-9ed7-802c1031900e · outbound

This paper cites Common information based markov perfect equilibria for linear-gaussian games with asymmetric information.

Provable Partially Observable Reinforcement Learning with Privileged Information Common information based markov perfect equilibria for linear-gaussian games with asymmetric information

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.238544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cedc9884-654f-48df-a2a5-a4435ef11285 · outbound

This paper cites Poste- rior sampling for competitive rl: Function approximation and partial observation.

Provable Partially Observable Reinforcement Learning with Privileged Information Poste- rior sampling for competitive rl: Function approximation and partial observation

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.226186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fa8a4d42-0c85-45f8-aa69-ebeebc845115 · outbound

This paper cites Learning to communicate with deep multi-agent reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Learning to communicate with deep multi-agent reinforcement learning

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.213731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2231e7d5-4078-439a-8c17-b7b62cfe3929 · outbound

This paper cites Computationally efficient pac rl in pomdps with latent determinism and conditional embeddings.

Provable Partially Observable Reinforcement Learning with Privileged Information Computationally efficient pac rl in pomdps with latent determinism and conditional embeddings

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.201238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation e14c806f-8f65-42cf-9715-667326470196 · outbound

This paper cites Actor-critic algorithms.

Provable Partially Observable Reinforcement Learning with Privileged Information Actor-critic algorithms

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.186967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 82d5fc1e-41a3-4ca6-8134-d17fa4c918e2 · outbound

This paper cites Provably e fficient exploration in policy optimization.

Provable Partially Observable Reinforcement Learning with Privileged Information Provably e fficient exploration in policy optimization

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.173029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 31f7914a-92bf-4466-a3a6-50437b3e9e20 · outbound

This paper cites Optimistic policy optimization with bandit feedback.

Provable Partially Observable Reinforcement Learning with Privileged Information Optimistic policy optimization with bandit feedback

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.159754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c73b445d-dab2-4326-8fb5-54831e4d0d0f · outbound

This paper cites Proximal Policy Optimization Algorithms.

Provable Partially Observable Reinforcement Learning with Privileged Information Proximal Policy Optimization Algorithms

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.660877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b321497-10f6-4430-a6b4-a709545abb65 · outbound

This paper cites A natural policy gradient.

Provable Partially Observable Reinforcement Learning with Privileged Information A natural policy gradient

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.146247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 3c907966-e501-4a25-b882-e415f34b9484 · outbound

This paper cites Optimality and approxi- mation with policy gradient methods in Markov decision processes.

Provable Partially Observable Reinforcement Learning with Privileged Information Optimality and approxi- mation with policy gradient methods in Markov decision processes

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.131943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 292cda01-7a8f-4ac7-a0f0-cfb0b2c95d91 · outbound

This paper cites Information state embedding in partially observable cooperative multi-agent reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Information state embedding in partially observable cooperative multi-agent reinforcement learning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.119280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c95e5aa1-8890-4093-9d8c-740e3d16bc7e · outbound

This paper cites Approximate infor- mation state for approximate planning and reinforcement learning in partially observed sys- tems.

Provable Partially Observable Reinforcement Learning with Privileged Information Approximate infor- mation state for approximate planning and reinforcement learning in partially observed sys- tems

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.106613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c9bc6d5d-eefc-4818-be95-83c0487b7a49 · outbound

This paper cites Stochastic games with one step delay sharing information pattern with application to power control.

Provable Partially Observable Reinforcement Learning with Privileged Information Stochastic games with one step delay sharing information pattern with application to power control

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.094199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9e3bb496-8db5-4244-830e-f8d3f22febbf · outbound

This paper cites A mea- surement study of internet delay asymmetry.

Provable Partially Observable Reinforcement Learning with Privileged Information A mea- surement study of internet delay asymmetry

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.081640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 6d2cb1c1-a240-4700-9c95-5033cda07d6b · outbound

This paper cites Repeated games with incomplete information.

Provable Partially Observable Reinforcement Learning with Privileged Information Repeated games with incomplete information

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.687754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 254b8c83-d1ab-4357-a907-d2f66ae616c0 · outbound

This paper cites Information theory: From coding to learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Information theory: From coding to learning

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.060933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 67936a39-66f6-4d20-b77b-b4d56d62b14f · outbound

This paper cites On Value Functions and the Agent-Environment Boundary.

Provable Partially Observable Reinforcement Learning with Privileged Information On Value Functions and the Agent-Environment Boundary

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.695389Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c07b385-7de8-4e98-8727-ce3a58b94cd4 · outbound

This paper cites A short note on learning discrete distributions.

Provable Partially Observable Reinforcement Learning with Privileged Information A short note on learning discrete distributions

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.699272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2580b214-3fde-481e-aa8e-d04beaee22e3 · outbound

This paper cites A characteri- zation of multiclass learnability, 2022.

Provable Partially Observable Reinforcement Learning with Privileged Information A characteri- zation of multiclass learnability, 2022

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.048694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cffa59e6-104b-47c8-99c6-0c4b76a227a0 · outbound

This paper cites A characteriza- tion of multiclass learnability.

Provable Partially Observable Reinforcement Learning with Privileged Information A characteriza- tion of multiclass learnability

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.036051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 88707e5b-c738-43f6-a625-0f666337a471 · outbound

This paper cites Approximately optimal approximate reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Approximately optimal approximate reinforcement learning

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.023529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation db7590f0-0b5f-43a8-81bb-880ea14462cf · outbound

This paper cites Convex optimization: Algorithms and complexity.

Provable Partially Observable Reinforcement Learning with Privileged Information Convex optimization: Algorithms and complexity

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:58.010854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c550fa58-6a96-4029-9677-f99375c1814a · outbound

This paper cites Tighter problem-dependent regret bounds in reinforce- ment learning without domain knowledge using value function bounds.

Provable Partially Observable Reinforcement Learning with Privileged Information Tighter problem-dependent regret bounds in reinforce- ment learning without domain knowledge using value function bounds

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:57.997919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b84e87ff-29a4-42be-843a-e0b026fa63cb · outbound

This paper cites Reward-free exploration for reinforcement learning.

Provable Partially Observable Reinforcement Learning with Privileged Information Reward-free exploration for reinforcement learning

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:57.984880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a754894a-2951-40e7-909b-970f2e2adf3b · outbound

This paper cites Is Q-learning provably efficient? In Advances in Neural Information Processing Systems, pages 4863–4873, 2018.

Provable Partially Observable Reinforcement Learning with Privileged Information Is Q-learning provably efficient? In Advances in Neural Information Processing Systems, pages 4863–4873, 2018

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:57.971151Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation c3b66ef2-81f7-40af-ad94-b46acf6a31e8 · outbound

This paper cites No-regret learning in convex games.

Provable Partially Observable Reinforcement Learning with Privileged Information No-regret learning in convex games

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:57.958482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 2822478c-8fe3-4201-995a-0bdb4b02f0e7 · outbound

This paper cites No-regret learning in bayesian games.

Provable Partially Observable Reinforcement Learning with Privileged Information No-regret learning in bayesian games

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:57.945880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1b60dc6e-6f1f-43bb-bd5c-1f1a7e5e29ab · outbound

This paper cites Bayes correlated equilibria, no-regret dynamics in Bayesian games, and the price of anarchy.

Provable Partially Observable Reinforcement Learning with Privileged Information Bayes correlated equilibria, no-regret dynamics in Bayesian games, and the price of anarchy

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-12T05:00:57.737884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3edf6af-5c31-413e-a19b-9db9d4b3320c · outbound

This paper cites By pluggingLt−1(π) into Equation (C.1), with simple algebric manipulations, we prove that: πt h(·|τh)∝πt−1 h (·|τh)exp ηEsh∼bh(τh) h Qt−1 h (τh,sh,·) i.

Provable Partially Observable Reinforcement Learning with Privileged Information By pluggingLt−1(π) into Equation (C.1), with simple algebric manipulations, we prove that: πt h(·|τh)∝πt−1 h (·|τh)exp ηEsh∼bh(τh) h Qt−1 h (τh,sh,·) i

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T05:00:57.933014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 1032c0d1-fd32-4015-a79e-d617f6fb4d71 · outbound

This paper cites bV (mi⋄πk i )⊙πk −i,G i,h+1 (ch+1) # ,H−h + 1 ) , where the last step is by inductive hypothesis. Now note that for anysh,ph,ah, we have bk−1 h (sh,ah) +Eoh+1∼bJk−1 h (·|sh,ah).

Provable Partially Observable Reinforcement Learning with Privileged Information bV (mi⋄πk i )⊙πk −i,G i,h+1 (ch+1) # ,H−h + 1 ) , where the last step is by inductive hypothesis. Now note that for anysh,ph,ah, we have bk−1 h (sh,ah) +Eoh+1∼bJk−1 h (·|sh,ah)

Reference 95

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T05:00:57.920214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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