:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Brandner, Dean, Lucia, Sergio
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Systems and Control
Online Access:	https://arxiv.org/abs/2511.16297
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Reinforced Model Predictive Control via Trust-Region Quasi-Newton Policy Optimization
by: Brandner, Dean, et al.
Published: (2024)

Computationally efficient Gauss-Newton reinforcement learning for model predictive control
by: Brandner, Dean, et al.
Published: (2025)

Quasi-Newton Compatible Actor-Critic for Deterministic Policies
by: Kordabad, Arash Bahari, et al.
Published: (2025)

Model-free Reinforcement Learning for Model-based Control: Towards Safe, Interpretable and Sample-efficient Agents
by: Banker, Thomas, et al.
Published: (2025)

Offline Guarded Safe Reinforcement Learning for Medical Treatment Optimization Strategies
by: Yan, Runze, et al.
Published: (2025)

A Safe Reinforcement Learning Algorithm for Supervisory Control of Power Plants
by: Sun, Yixuan, et al.
Published: (2024)

Intersection of Reinforcement Learning and Bayesian Optimization for Intelligent Control of Industrial Processes: A Safe MPC-based DPG using Multi-Objective BO
by: Esfahani, Hossein Nejatbakhsh, et al.
Published: (2025)

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

Constrained Reinforcement Learning for Safe Heat Pump Control
by: Zhang, Baohe, 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)

Safe Reinforcement Learning-Based Vibration Control: Overcoming Training Risks with LQR Guidance
by: Thorat, Rohan Vitthal, et al.
Published: (2025)

Safe Online Control-Informed Learning
by: Zhou, Tianyu, et al.
Published: (2025)

LexiSafe: Offline Safe Reinforcement Learning with Lexicographic Safety-Reward Hierarchy
by: Yang, Hsin-Jung, et al.
Published: (2026)

Feasible Policy Iteration for Safe Reinforcement Learning
by: Yang, Yujie, et al.
Published: (2023)

Safe and Robust Reinforcement Learning: Principles and Practice
by: Yamagata, Taku, et al.
Published: (2024)

Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
by: Prajapat, Manish, et al.
Published: (2025)

Safe Reinforcement Learning with Minimal Supervision
by: Quessy, Alexander, et al.
Published: (2025)

DeepSafeMPC: Deep Learning-Based Model Predictive Control for Safe Multi-Agent Reinforcement Learning
by: Wang, Xuefeng, et al.
Published: (2024)

Kernel-Based Safe Exploration in Deep Reinforcement Learning
by: Majumdar, Rupak, et al.
Published: (2026)

Safe Learning-Based Optimization of Model Predictive Control: Application to Battery Fast-Charging
by: Hirt, Sebastian, et al.
Published: (2024)

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
by: Lederer, Armin, et al.
Published: (2019)

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

Safe and Near-Optimal Control with Online Dynamics Learning
by: Prajapat, Manish, et al.
Published: (2025)

Trustworthy and Explainable Deep Reinforcement Learning for Safe and Energy-Efficient Process Control: A Use Case in Industrial Compressed Air Systems
by: Bezold, Vincent, et al.
Published: (2025)

Provable Traffic Rule Compliance in Safe Reinforcement Learning on the Open Sea
by: Krasowski, Hanna, et al.
Published: (2024)

Safe Multi-Agent Reinforcement Learning with Convergence to Generalized Nash Equilibrium
by: Li, Zeyang, et al.
Published: (2024)

Myopically Verifiable Probabilistic Certificates for Safe Control and Learning
by: Wang, Zhuoyuan, et al.
Published: (2024)

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

Optimal Parameter Adaptation for Safety-Critical Control via Safe Barrier Bayesian Optimization
by: Wang, Shengbo, et al.
Published: (2025)

Recursively Feasible Probabilistic Safe Online Learning with Control Barrier Functions
by: Castañeda, Fernando, et al.
Published: (2022)

Foundations of Safe Online Reinforcement Learning in the Linear Quadratic Regulator: $\sqrt{T}$-Regret
by: Schiffer, Benjamin, et al.
Published: (2025)

Foundations of Safe Online Reinforcement Learning in the Linear Quadratic Regulator: Generalized Baselines
by: Schiffer, Benjamin, et al.
Published: (2024)

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?
by: Cheng, Xiaoyuan, et al.
Published: (2026)

Safe Gradient Flow for Bilevel Optimization
by: Sharifi, Sina, et al.
Published: (2025)

Safe PDE Boundary Control with Neural Operators
by: Hu, Hanjiang, et al.
Published: (2024)

Safely Learning Dynamical Systems
by: Ahmadi, Amir Ali, et al.
Published: (2023)

GenSafe: A Generalizable Safety Enhancer for Safe Reinforcement Learning Algorithms Based on Reduced Order Markov Decision Process Model
by: Zhou, Zhehua, et al.
Published: (2024)

Approximate Model-Based Shielding for Safe Reinforcement Learning
by: Goodall, Alexander W., et al.
Published: (2023)

Privacy-Preserving Federated Learning Framework for Distributed Chemical Process Optimization
by: Pipattaratonchai, Teetat, et al.
Published: (2026)

Deep Reinforcement Learning with Enhanced PPO for Safe Mobile Robot Navigation
by: Taheri, Hamid, et al.
Published: (2024)