Cover Image

Resilient Constrained Reinforcement Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ding, Dongsheng, Huan, Zhengyan, Ribeiro, Alejandro
Format:	Preprint
Published:	2023
Subjects:	Optimization and Control Machine Learning Systems and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Last-Iterate Convergent Policy Gradient Primal-Dual Methods for Constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2023)

Alignment of large language models with constrained learning
by: Zhang, Botong, et al.
Published: (2025)

Meta-Learning for Physically-Constrained Neural System Identification
by: Chakrabarty, Ankush, et al.
Published: (2025)

Federated Learning Forecasting for Strengthening Grid Reliability and Enabling Markets for Resilience
by: Pereira, Lucas, et al.
Published: (2024)

HUANet: Hard-Constrained Unrolled ADMM for Constrained Convex Optimization
by: Tran, Trinh, et al.
Published: (2026)

On the Foundation of Distributionally Robust Reinforcement Learning
by: Wang, Shengbo, et al.
Published: (2023)

Constrained Diffusion Models via Dual Training
by: Khalafi, Shervin, et al.
Published: (2024)

Offline Reinforcement Learning via Inverse Optimization
by: Dimanidis, Ioannis, et al.
Published: (2025)

Offline Hierarchical Reinforcement Learning via Inverse Optimization
by: Schmidt, Carolin, et al.
Published: (2024)

Optimism as Risk-Seeking in Multi-Agent Reinforcement Learning
by: Zhang, Runyu, et al.
Published: (2025)

Operator Models for Continuous-Time Offline Reinforcement Learning
by: Hoischen, Nicolas, et al.
Published: (2025)

Convergence and stability of Q-learning in Hierarchical Reinforcement Learning
by: Manenti, Massimiliano, et al.
Published: (2025)

Towards Fast Rates for Federated and Multi-Task Reinforcement Learning
by: Zhu, Feng, et al.
Published: (2024)

Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
by: Zhang, Chenyu, et al.
Published: (2024)

Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design
by: Takubo, Yuji, et al.
Published: (2021)

Action Dependency Graphs for Globally Optimal Coordinated Reinforcement Learning
by: Ding, Jianglin, et al.
Published: (2025)

Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control
by: Kato, Teruki, et al.
Published: (2026)

Conformal Predictive Programming for Chance Constrained Optimization
by: Zhao, Yiqi, et al.
Published: (2024)

Online Reinforcement Learning in Markov Decision Process Using Linear Programming
by: Leon, Vincent, et al.
Published: (2023)

Sample Complexity of the Linear Quadratic Regulator: A Reinforcement Learning Lens
by: Moghaddam, Amirreza Neshaei, et al.
Published: (2024)

The Sample Complexity of Online Reinforcement Learning: A Multi-model Perspective
by: Muehlebach, Michael, et al.
Published: (2025)

Reinforcement Learning-based Control via Y-wise Affine Neural Networks (YANNs)
by: Braniff, Austin, et al.
Published: (2025)

Convergence and sample complexity of natural policy gradient primal-dual methods for constrained MDPs
by: Ding, Dongsheng, et al.
Published: (2022)

Temporal-Aware Deep Reinforcement Learning for Energy Storage Bidding in Energy and Contingency Reserve Markets
by: Li, Jinhao, et al.
Published: (2024)

Response-Aware Risk-Constrained Control Barrier Function With Application to Vehicles
by: Liao, Qijun, et al.
Published: (2026)

Semi-on-Demand Transit Feeders with Shared Autonomous Vehicles and Reinforcement-Learning-Based Zonal Dispatching Control
by: Ng, Max T. M., et al.
Published: (2025)

Attentive Convolutional Deep Reinforcement Learning for Optimizing Solar-Storage Systems in Real-Time Electricity Markets
by: Li, Jinhao, et al.
Published: (2024)

Precise Insulin Delivery for Artificial Pancreas: A Reinforcement Learning Optimized Adaptive Fuzzy Control Approach
by: Mameche, Omar, et al.
Published: (2025)

Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG
by: Chang, Ting-Jui, et al.
Published: (2024)

SINDy-RL: Interpretable and Efficient Model-Based Reinforcement Learning
by: Zolman, Nicholas, et al.
Published: (2024)

Reinforcement Learning-based Control via Y-wise Affine Neural Networks: Comparative Case Studies for Chemical Processes
by: Braniff, Austin, et al.
Published: (2026)

Neural Contraction Metrics with Formal Guarantees for Discrete-Time Nonlinear Dynamical Systems
by: Li, Haoyu, et al.
Published: (2025)

Structured Cooperative Multi-Agent Reinforcement Learning: a Bayesian Network Perspective
by: Syed, Shahbaz P Qadri, et al.
Published: (2025)

MPC-Inspired Reinforcement Learning for Verifiable Model-Free Control
by: Lu, Yiwen, et al.
Published: (2023)

Dynamic Rolling Horizon Optimization for Network-Constrained V2X Value Stacking of Electric Vehicles Under Uncertainties
by: Jiang, Canchen, et al.
Published: (2025)

Risk-Aware Safe Reinforcement Learning for Control of Stochastic Linear Systems
by: Esmaeili, Babak, et al.
Published: (2025)

Certifying Stability of Reinforcement Learning Policies using Generalized Lyapunov Functions
by: Long, Kehan, et al.
Published: (2025)

GreenLight-Gym: Reinforcement learning benchmark environment for control of greenhouse production systems
by: van Laatum, Bart, et al.
Published: (2024)

Faster Reinforcement Learning by Freezing Slow States
by: Wang, Yijia, et al.
Published: (2023)

Temporal Difference Learning with Compressed Updates: Error-Feedback meets Reinforcement Learning
by: Mitra, Aritra, et al.
Published: (2023)