Paper Citation Record · LEDGER

Practical Risk Measures in Reinforcement Learning

As of 16 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:1908.08379.

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

pith.paper-citation-record.v1
1908.08379 v1

Coverage vector

measured 44 of 44 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

44 of 44 outbound references displayed

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External citation measurements

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Outbound references

Observation c0622a28-0221-4059-bcb0-06077b7047cb · outbound

This paper cites Constrained Policy Optimization.

Practical Risk Measures in Reinforcement Learning Constrained Policy Optimization

Reference 1

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Practical Risk Measures in Reinforcement Learning Unresolved cited work

Reference 9

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Observation 6885c0a8-87ad-4c34-99eb-9d5749067e16 · outbound

This paper cites A comprehensive survey on safe reinforce- ment learning.

Practical Risk Measures in Reinforcement Learning A comprehensive survey on safe reinforce- ment learning

Reference 12

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This paper cites Risk-sensitive reinforcement learning applied to control under constraints.

Practical Risk Measures in Reinforcement Learning Risk-sensitive reinforcement learning applied to control under constraints

Reference 13

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This paper cites Likelihood ratio gradient es- timation for stochastic systems.

Practical Risk Measures in Reinforcement Learning Likelihood ratio gradient es- timation for stochastic systems

Reference 14

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This paper cites Risk-sensitive markov decision processes.

Practical Risk Measures in Reinforcement Learning Risk-sensitive markov decision processes

Reference 16

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Observation f1d830a1-cbc2-4f20-bc2a-93589db2b562 · outbound

This paper cites Func- tional value iteration for decision-theoretic planning with general utility functions.

Practical Risk Measures in Reinforcement Learning Func- tional value iteration for decision-theoretic planning with general utility functions

Reference 22

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This paper cites Mean-Variance Optimization in Markov Decision Processes.

Practical Risk Measures in Reinforcement Learning Mean-Variance Optimization in Markov Decision Processes

Reference 25

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This paper cites Safe Exploration in Markov Decision Processes.

Practical Risk Measures in Reinforcement Learning Safe Exploration in Markov Decision Processes

Reference 28

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This paper cites Parametric Return Density Estimation for Reinforcement Learning.

Practical Risk Measures in Reinforcement Learning Parametric Return Density Estimation for Reinforcement Learning

Reference 29

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Observation 49cffd99-260f-496f-a1bc-ca950d320464 · outbound

This paper cites Policy invariance under reward transformations: Theory and application to reward shaping.

Practical Risk Measures in Reinforcement Learning Policy invariance under reward transformations: Theory and application to reward shaping

Reference 30

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This paper cites Markov chains.

Practical Risk Measures in Reinforcement Learning Markov chains

Reference 31

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Observation 80b9dabf-59c1-41ee-ac76-8122aa2ad39d · outbound

This paper cites Evaluation: from preci- sion, recall and f-measure to roc, informedness, markedness and correlation.

Practical Risk Measures in Reinforcement Learning Evaluation: from preci- sion, recall and f-measure to roc, informedness, markedness and correlation

Reference 33

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Observation 6d394dd3-f44e-4bad-a12a-7656b895fecb · outbound

This paper cites Actor-critic algorithms for risk- sensitive mdps.

Practical Risk Measures in Reinforcement Learning Actor-critic algorithms for risk- sensitive mdps

Reference 34

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This paper cites Markov decision pro- cesses.

Practical Risk Measures in Reinforcement Learning Markov decision pro- cesses

Reference 35

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This paper cites Td algorithm for the variance of return and mean-variance reinforcement learning.

Practical Risk Measures in Reinforcement Learning Td algorithm for the variance of return and mean-variance reinforcement learning

Reference 37

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This paper cites Lectures on stochastic program- ming: modeling and theory.

Practical Risk Measures in Reinforcement Learning Lectures on stochastic program- ming: modeling and theory

Reference 38

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Observation 60c9b40d-6e7d-4333-af3c-1fa87fb43545 · outbound

This paper cites Temporal difference methods for the variance of the reward to go.

Practical Risk Measures in Reinforcement Learning Temporal difference methods for the variance of the reward to go

Reference 43

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Observation 1d70e6be-1833-424a-8977-010079b7e4bf · outbound

This paper cites The gambler’s ruin ap- proach to business risk.

Practical Risk Measures in Reinforcement Learning The gambler’s ruin ap- proach to business risk

Reference 44

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Practical Risk Measures in Reinforcement Learning Unresolved cited work

Reference 1186

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Observation 9e94c784-f3a5-42a1-9e30-acec831f94d4 · outbound

This paper cites Dynamic probabilistic systems: Markov models, volume.

Practical Risk Measures in Reinforcement Learning Dynamic probabilistic systems: Markov models, volume

Reference 1972

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Observation d0cb7324-dce7-49bf-bf05-d3ffd12d5fa2 · outbound

This paper cites Percentile performance criteria for limit- ing average markov decision processes.

Practical Risk Measures in Reinforcement Learning Percentile performance criteria for limit- ing average markov decision processes

Reference 1974

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:47:01.212764Z

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Observation 47e56ef4-44d9-4e50-8ad3-296d7d0ff9cc · outbound

This paper cites Reinforcement learning: An introduction.

Practical Risk Measures in Reinforcement Learning Reinforcement learning: An introduction

Reference 1982

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This paper cites Policy gradients with variance related risk criteria.

Practical Risk Measures in Reinforcement Learning Policy gradients with variance related risk criteria

Reference 1988

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Observation 24f94fc6-a7ea-4083-a22b-da5919f98226 · outbound

This paper cites Deep learning, vol- ume.

Practical Risk Measures in Reinforcement Learning Deep learning, vol- ume

Reference 1990

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Source-reported events for the cited work

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Observation fc743c7c-1e30-4516-a20a-4fe2e007a427 · outbound

This paper cites Optimization of conditional value-at-risk.

Practical Risk Measures in Reinforcement Learning Optimization of conditional value-at-risk

Reference 1994

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This paper cites Monte Carlo: concepts, algorithms, and applications.

Practical Risk Measures in Reinforcement Learning Monte Carlo: concepts, algorithms, and applications

Reference 1995

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Source-reported events for the cited work

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Observation fe836923-52ea-4ca8-991f-ffbd96e51f10 · outbound

This paper cites Safe policy iteration.

Practical Risk Measures in Reinforcement Learning Safe policy iteration

Reference 1998

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Source-reported events for the cited work

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Observation 3e7b3fcc-7d6c-457f-9554-80bac6e4a827 · outbound

This paper cites Safe policy search for lifelong reinforce- ment learning with sublinear regret.

Practical Risk Measures in Reinforcement Learning Safe policy search for lifelong reinforce- ment learning with sublinear regret

Reference 1999

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Observation 9659f2d8-4bff-4b40-9f93-49a21b1bd4c9 · outbound

This paper cites Stochastic approximation and recursive algorithms and applications, volume.

Practical Risk Measures in Reinforcement Learning Stochastic approximation and recursive algorithms and applications, volume

Reference 2000

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This paper cites Dy- namic programming and optimal control, volume.

Practical Risk Measures in Reinforcement Learning Dy- namic programming and optimal control, volume

Reference 2001

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This paper cites Human-level control through deep reinforcement learning.

Practical Risk Measures in Reinforcement Learning Human-level control through deep reinforcement learning

Reference 2002

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Practical Risk Measures in Reinforcement Learning Deep learning

Reference 2003

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Observation 82567b9a-80e6-4a58-ae6f-01dd20053b60 · outbound

This paper cites Model predictive control.

Practical Risk Measures in Reinforcement Learning Model predictive control

Reference 2005

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Observation c4994c29-6bdb-441c-a921-5c0017937f81 · outbound

This paper cites Existence and Finiteness Conditions for Risk-Sensitive Planning: Results and Conjectures.

Practical Risk Measures in Reinforcement Learning Existence and Finiteness Conditions for Risk-Sensitive Planning: Results and Conjectures

Reference 2006

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Observation 98a3397f-b14f-427d-b44e-c62e1e69eb7c · outbound

This paper cites The variance of discounted markov decision processes.

Practical Risk Measures in Reinforcement Learning The variance of discounted markov decision processes

Reference 2009

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Observation d88b01fb-298f-40c1-a244-7d19c6fc2aef · outbound

This paper cites Risk-sensitive reinforcement learning.

Practical Risk Measures in Reinforcement Learning Risk-sensitive reinforcement learning

Reference 2011

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Observation a8c73675-244b-4b88-bef3-af6ef33686bd · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Practical Risk Measures in Reinforcement Learning Adam: A Method for Stochastic Optimization

Reference 2012

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Practical Risk Measures in Reinforcement Learning Risk-constrained reinforcement learning with percentile risk criteria

Reference 2013

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Practical Risk Measures in Reinforcement Learning Actor-critic algorithms

Reference 2014

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Observation 1b2a7ee7-e7c6-4da9-b510-610e36ec7c36 · outbound

This paper cites Concrete Problems in AI Safety.

Practical Risk Measures in Reinforcement Learning Concrete Problems in AI Safety

Reference 2015

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Observation 667f2c22-fb2c-40f6-b2e6-5872d5282a4e · outbound

This paper cites Inﬁnite-horizon policy-gradient estimation.

Practical Risk Measures in Reinforcement Learning Inﬁnite-horizon policy-gradient estimation

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:47:01.294961Z

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Observation c953d1a8-b7ee-4404-bf53-d5e7271a4d22 · outbound

This paper cites Constrained Markov decision processes, volume.

Practical Risk Measures in Reinforcement Learning Constrained Markov decision processes, volume

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:47:01.328689Z

Source-reported events for the cited work

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Observation 111b9753-ed5f-4a49-8c6d-1349bb516e05 · outbound

This paper cites Learning to predict by the methods of temporal differences.

Practical Risk Measures in Reinforcement Learning Learning to predict by the methods of temporal differences

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:47:00.734699Z

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