Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning | Paper Citation Record

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This paper cites The reality gap in robotics: Challenges, solutions, and best practices.Annual Review of Control, Robotics, and Autonomous Systems, 9:403–432, 2026.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning The reality gap in robotics: Challenges, solutions, and best practices.Annual Review of Control, Robotics, and Autonomous Systems, 9:403–432, 2026

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning State entropy regularization for robust reinforcement learning

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This paper cites Algorithmic market making in dealer markets with hedging and market impact.Mathematical Finance, 33(1):41–79, 2023.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Algorithmic market making in dealer markets with hedging and market impact.Mathematical Finance, 33(1):41–79, 2023

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time q-learning in jump-diffusion models under Tsallis entropy, 2024

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Unresolved cited work

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This paper cites Robust multi-agent reinforcement learning via adversarial regularization: Theoretical foundation and stable algorithms.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Robust multi-agent reinforcement learning via adversarial regularization: Theoretical foundation and stable algorithms

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This paper cites Cambridge University Press, 2015.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Cambridge University Press, 2015

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This paper cites Robust reinforcement learning with general utility.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Robust reinforcement learning with general utility

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Deterministic policy gradient for reinforcement learning with continuous time and state, 2026

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This paper cites Dai and Mark Gluzman.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Dai and Mark Gluzman

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This paper cites Twice regularized MDPs and the equivalence between robustness and regularization.Advances in Neural Information Processing Systems, 34:22274–22287, 2021.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Twice regularized MDPs and the equivalence between robustness and regularization.Advances in Neural Information Processing Systems, 34:22274–22287, 2021

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Robustness and regularization in rein- forcement learning

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This paper cites Entropy regularization in mean-field games of optimal stopping.arXiv preprint arXiv:2509.18821, 2025.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Entropy regularization in mean-field games of optimal stopping.arXiv preprint arXiv:2509.18821, 2025

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This paper cites Donsker and S.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Donsker and S

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Maximum entropy RL (provably) solves some robust RL problems

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Actor-critic learning for mean-field control in continuous time.Journal of Machine Learning Research, 26(127):1–42, 2025

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Reinforcement learning for jump-diffusions, with financial applications.Mathematical Finance, 2026

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning A theory of regularized Markov decision processes

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Convergence of policy gradient methods for finite-horizon exploratory linear-quadratic control problems.SIAM Journal on Control and Optimization, 62(2):1060–1092, 2024

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Scalable first-order methods for robust MDPs

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time Markov decision processes

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Entropy regularization for mean field games with learning

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Soft Actor-Critic Algorithms and Applications

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time reinforcement learning for optimal switching over multiple regimes, 2025

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Regularized policies are reward robust

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time risk-sensitive reinforcement learning via quadratic variation penalty.Applied Mathematics & Optimization, 93(2):58, 2026

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Accuracy of discretely sampled stochastic policies in continuous-time reinforcement learning.arXiv preprint arXiv:2503.09981, 2025

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy evaluation and temporal-difference learning in continuous time and space: A martingale approach.Journal of Machine Learning Research, 23(154):1–55, 2022

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy gradient and actor-critic learning in continuous time and space: Theory and algorithms.Journal of Machine Learning Research, 23(275):1–50, 2022

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning q-learning in continuous time.Journal of Machine Learning Research, 24(161):1–61, 2023

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning A Fisher–Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces.Foundations of Computational Mathematics, pages 1–75, 2025

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy gradient for rectangular robust Markov decision processes

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy mirror descent for reinforcement learning: Linear convergence, new sampling complexity, and generalized problem classes.Mathematical Programming, 198:1059–1106, 2023

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy gradient algorithms for robust MDPs with nonrectan- gular uncertainty sets.SIAM Journal on Optimization, 36(1):120–151, 2026

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Springer, 2007

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Sim-to-real transfer of robotic control with dynamics randomization

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Puterman.Markov Decision Processes: Discrete Stochastic Dynamic Programming

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning On stochastic optimal control and reinforcement learning by approximate inference

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Regularity and stability of feedback relaxed controls.SIAM Journal on Control and Optimization, 59(5):3118–3151, 2021

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time q-learning for mean-field control with common noise, part-I: Theoretical foundations, 2026

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time q-learning for mean-field control with common noise, part-II: q-learning algorithms, 2026

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Trust region policy optimization

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Proximal Policy Optimization Algorithms

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Optimal scheduling of entropy regularizer for continuous-time linear-quadratic reinforcement learning.SIAM Journal on Control and Optimization, 62(1):135–166, 2024

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Action robust reinforcement learning and applications in continuous control

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This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Domain randomization for transferring deep neural networks from simulation to the real world

Reference 57

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This paper cites Linearly-solvable Markov decision problems.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Linearly-solvable Markov decision problems

Reference 58

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Observation 728b9346-1ba6-458b-929c-e14820ffab7e · outbound

This paper cites Policy gradient in robust MDPs with global convergence guarantee.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy gradient in robust MDPs with global convergence guarantee

Reference 59

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Observation f47cd47e-76b9-4c6c-9834-2e89455c1353 · outbound

This paper cites Continuous time q-learning for mean-field control problems.Applied Mathematics & Optimization, 91(1):10, 2025.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous time q-learning for mean-field control problems.Applied Mathematics & Optimization, 91(1):10, 2025

Reference 60

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Observation f8a690eb-adaf-4ca4-9737-ea0cfcbac422 · outbound

This paper cites Robust Markov decision processes.Mathematics of Operations Research, 38(1):153–183, 2013.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Robust Markov decision processes.Mathematics of Operations Research, 38(1):153–183, 2013

Reference 61

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Observation 98aeb53b-fa58-4097-b5d6-79ff899e23cf · outbound

This paper cites Continuous-time q-learning for Markov regime switching system under Tsallis entropy, 2026.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Continuous-time q-learning for Markov regime switching system under Tsallis entropy, 2026

Reference 62

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This paper cites Policy optimization for continuous reinforcement learning.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Policy optimization for continuous reinforcement learning

Reference 63

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This paper cites X s∈S ¯dπ ρ(s) X a∈As µ(a|s) exp R(s, a)−R ˜θ∗(s, a) τ # =τlog.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning X s∈S ¯dπ ρ(s) X a∈As µ(a|s) exp R(s, a)−R ˜θ∗(s, a) τ # =τlog

Reference 64

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This paper cites The test statistic is t= WC(πτ)−WC(π std)q SE2 τ + SE2 0 , where SEτ and SE0 are the standard errors (across seeds) at the respective worst-case grid cells.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning The test statistic is t= WC(πτ)−WC(π std)q SE2 τ + SE2 0 , where SEτ and SE0 are the standard errors (across seeds) at the respective worst-case grid cells

Reference 65

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This paper cites In both market making and queueing, performance peaks at an intermediate∆t and degrades for both coarser and finer grids.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning In both market making and queueing, performance peaks at an intermediate∆t and degrades for both coarser and finer grids

Reference 66

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Observation 33d1054c-1eed-4d66-b8cf-0d8aa0590d72 · outbound

This paper cites The arrival-driven implementation has no grid resolution hyperparameter.

Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning The arrival-driven implementation has no grid resolution hyperparameter

Reference 67

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Entropy Regularization Improves Policy Robustness in Continuous-Time Reinforcement Learning Unresolved cited work

Reference 68

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