Guardado en:
| Autores principales: | Zhang, Yifan, Zheng, Liang |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.16170 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
RE-SAC: Disentangling aleatoric and epistemic risks in bus fleet control: A stable and robust ensemble DRL approach
por: Zhang, Yifan, et al.
Publicado: (2026)
por: Zhang, Yifan, et al.
Publicado: (2026)
A unifying framework for generalised Bayesian online learning in non-stationary environments
por: Duran-Martin, Gerardo, et al.
Publicado: (2024)
por: Duran-Martin, Gerardo, et al.
Publicado: (2024)
Generalized Bayesian deep reinforcement learning
por: Roy, Shreya Sinha, et al.
Publicado: (2024)
por: Roy, Shreya Sinha, et al.
Publicado: (2024)
Position: Lifetime tuning is incompatible with continual reinforcement learning
por: Mesbahi, Golnaz, et al.
Publicado: (2024)
por: Mesbahi, Golnaz, et al.
Publicado: (2024)
Quantum reinforcement learning in continuous action space
por: Wu, Shaojun, et al.
Publicado: (2020)
por: Wu, Shaojun, et al.
Publicado: (2020)
Feature-driven reinforcement learning for photovoltaic in continuous intraday trading
por: Abate, Arega Getaneh, et al.
Publicado: (2025)
por: Abate, Arega Getaneh, et al.
Publicado: (2025)
Agile and versatile bipedal robot tracking control through reinforcement learning
por: Li, Jiayi, et al.
Publicado: (2024)
por: Li, Jiayi, et al.
Publicado: (2024)
Bayesian continual learning and forgetting in neural networks
por: Bonnet, Djohan, et al.
Publicado: (2025)
por: Bonnet, Djohan, et al.
Publicado: (2025)
On the stability of Lipschitz continuous control problems and its application to reinforcement learning
por: Cho, Namkyeong, et al.
Publicado: (2024)
por: Cho, Namkyeong, et al.
Publicado: (2024)
An adaptive transfer learning perspective on classification in non-stationary environments
por: Reeve, Henry W J
Publicado: (2024)
por: Reeve, Henry W J
Publicado: (2024)
Task diversity produces systematic transfer but inhibits continual reinforcement learning
por: Seth, Purab, et al.
Publicado: (2026)
por: Seth, Purab, et al.
Publicado: (2026)
Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces
por: Kamoutsi, Angeliki, et al.
Publicado: (2024)
por: Kamoutsi, Angeliki, et al.
Publicado: (2024)
Deep reinforcement learning for weakly coupled MDP's with continuous actions
por: Robledo, Francisco, et al.
Publicado: (2024)
por: Robledo, Francisco, et al.
Publicado: (2024)
Error-controlled non-additive interaction discovery in machine learning models
por: Chen, Winston, et al.
Publicado: (2024)
por: Chen, Winston, et al.
Publicado: (2024)
Experimental evaluation of offline reinforcement learning for HVAC control in buildings
por: Wang, Jun, et al.
Publicado: (2024)
por: Wang, Jun, et al.
Publicado: (2024)
Scores as Actions: a framework of fine-tuning diffusion models by continuous-time reinforcement learning
por: Zhao, Hanyang, et al.
Publicado: (2024)
por: Zhao, Hanyang, et al.
Publicado: (2024)
Adaptive trajectory-constrained exploration strategy for deep reinforcement learning
por: Wang, Guojian, et al.
Publicado: (2023)
por: Wang, Guojian, et al.
Publicado: (2023)
Transfer learning strategies for accelerating reinforcement-learning-based flow control
por: Salehi, Saeed
Publicado: (2025)
por: Salehi, Saeed
Publicado: (2025)
Normalization and effective learning rates in reinforcement learning
por: Lyle, Clare, et al.
Publicado: (2024)
por: Lyle, Clare, et al.
Publicado: (2024)
Model predictive control-based value estimation for efficient reinforcement learning
por: Wu, Qizhen, et al.
Publicado: (2023)
por: Wu, Qizhen, et al.
Publicado: (2023)
Ergodicity in reinforcement learning
por: Baumann, Dominik, et al.
Publicado: (2026)
por: Baumann, Dominik, et al.
Publicado: (2026)
A modular framework for stabilizing deep reinforcement learning control
por: Lawrence, Nathan P., et al.
Publicado: (2023)
por: Lawrence, Nathan P., et al.
Publicado: (2023)
Reinforcement learning with non-ergodic reward increments: robustness via ergodicity transformations
por: Baumann, Dominik, et al.
Publicado: (2023)
por: Baumann, Dominik, et al.
Publicado: (2023)
Application of linear regression and quasi-Newton methods to the deep reinforcement learning in continuous action cases
por: Komatsu, Hisato
Publicado: (2025)
por: Komatsu, Hisato
Publicado: (2025)
Reliably-stabilizing piecewise-affine neural network controllers
por: Fabiani, Filippo, et al.
Publicado: (2021)
por: Fabiani, Filippo, et al.
Publicado: (2021)
Computationally efficient Gauss-Newton reinforcement learning for model predictive control
por: Brandner, Dean, et al.
Publicado: (2025)
por: Brandner, Dean, et al.
Publicado: (2025)
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces
por: Duan, Yaqi, et al.
Publicado: (2024)
por: Duan, Yaqi, et al.
Publicado: (2024)
A Bayesian latent class reinforcement learning framework to capture adaptive, feedback-driven travel behaviour
por: Sfeir, Georges, et al.
Publicado: (2025)
por: Sfeir, Georges, et al.
Publicado: (2025)
How to craft a deep reinforcement learning policy for wind farm flow control
por: Kadoche, Elie, et al.
Publicado: (2025)
por: Kadoche, Elie, et al.
Publicado: (2025)
Total robustness in Bayesian Nonlinear Regression
por: Chen, Mengqi, et al.
Publicado: (2025)
por: Chen, Mengqi, et al.
Publicado: (2025)
Enhancing sample efficiency in reinforcement-learning-based flow control: replacing the critic with an adaptive reduced-order model
por: Yao, Zesheng, et al.
Publicado: (2026)
por: Yao, Zesheng, et al.
Publicado: (2026)
Leveraging LLMs for reward function design in reinforcement learning control tasks
por: Cardenoso, Franklin, et al.
Publicado: (2025)
por: Cardenoso, Franklin, et al.
Publicado: (2025)
Dynamic control of self-assembly of quasicrystalline structures through reinforcement learning
por: Lieu, Uyen Tu, et al.
Publicado: (2023)
por: Lieu, Uyen Tu, et al.
Publicado: (2023)
Multi-task learning via robust regularized clustering with non-convex group penalties
por: Okazaki, Akira, et al.
Publicado: (2024)
por: Okazaki, Akira, et al.
Publicado: (2024)
Koopman-based surrogate modeling for reinforcement-learning-control of Rayleigh-Benard convection
por: Plotzki, Tim, et al.
Publicado: (2026)
por: Plotzki, Tim, et al.
Publicado: (2026)
Multi-agent reinforcement learning for the control of three-dimensional Rayleigh-Bénard convection
por: Vasanth, Joel, et al.
Publicado: (2024)
por: Vasanth, Joel, et al.
Publicado: (2024)
Smoothed functional-based gradient algorithms for off-policy reinforcement learning: A non-asymptotic viewpoint
por: Vijayan, Nithia, et al.
Publicado: (2021)
por: Vijayan, Nithia, et al.
Publicado: (2021)
Decoding trust: A reinforcement learning perspective
por: Zheng, Guozhong, et al.
Publicado: (2023)
por: Zheng, Guozhong, et al.
Publicado: (2023)
An introduction to reinforcement learning for neuroscience
por: Jensen, Kristopher T.
Publicado: (2023)
por: Jensen, Kristopher T.
Publicado: (2023)
Optimistic Q-learning for average reward and episodic reinforcement learning
por: Agrawal, Priyank, et al.
Publicado: (2024)
por: Agrawal, Priyank, et al.
Publicado: (2024)
Ejemplares similares
-
RE-SAC: Disentangling aleatoric and epistemic risks in bus fleet control: A stable and robust ensemble DRL approach
por: Zhang, Yifan, et al.
Publicado: (2026) -
A unifying framework for generalised Bayesian online learning in non-stationary environments
por: Duran-Martin, Gerardo, et al.
Publicado: (2024) -
Generalized Bayesian deep reinforcement learning
por: Roy, Shreya Sinha, et al.
Publicado: (2024) -
Position: Lifetime tuning is incompatible with continual reinforcement learning
por: Mesbahi, Golnaz, et al.
Publicado: (2024) -
Quantum reinforcement learning in continuous action space
por: Wu, Shaojun, et al.
Publicado: (2020)