Cover Image

Computationally efficient Gauss-Newton reinforcement learning for model predictive control

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brandner, Dean, Gros, Sebastien, Lucia, Sergio
Format:	Preprint
Published:	2025
Subjects:	Systems and Control Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

Optimizing Operation Recipes with Reinforcement Learning for Safe and Interpretable Control of Chemical Processes
by: Brandner, Dean, et al.
Published: (2025)

Direct transfer of optimized controllers to similar systems using dimensionless MPC
by: Hromatko, Josip Kir, et al.
Published: (2025)

Exploiting inter-agent coupling information for efficient reinforcement learning of cooperative LQR
by: Syed, Shahbaz P Qadri, et al.
Published: (2025)

Data-assimilated model-informed reinforcement learning
by: Ozan, Defne E., et al.
Published: (2025)

A modular framework for stabilizing deep reinforcement learning control
by: Lawrence, Nathan P., et al.
Published: (2023)

Nonlinear sparse variational Bayesian learning based model predictive control with application to PEMFC temperature control
by: Zhang, Qi, et al.
Published: (2024)

A Riemannian Optimization Perspective of the Gauss-Newton Method for Feedforward Neural Networks
by: Cayci, Semih
Published: (2024)

Interpretable reinforcement learning for heat pump control through asymmetric differentiable decision trees
by: Van Puyvelde, Toon, et al.
Published: (2025)

Optimization of the Model Predictive Control Meta-Parameters Through Reinforcement Learning
by: Bøhn, Eivind, et al.
Published: (2021)

Distill2Explain: Differentiable decision trees for explainable reinforcement learning in energy application controllers
by: Gokhale, Gargya, et al.
Published: (2024)

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

Autonomous vehicle decision and control through reinforcement learning with traffic flow randomization
by: Lin, Yuan, et al.
Published: (2024)

Load constrained wind farm flow control through multi-objective multi-agent reinforcement learning
by: Åstrand, Teodor, et al.
Published: (2026)

Falsification-driven reinforcement learning for maritime motion planning
by: Müller, Marlon, et al.
Published: (2025)

Efficient model predictive control for nonlinear systems modelled by deep neural networks
by: Lan, Jianglin
Published: (2024)

Scalable spectral representations for multi-agent reinforcement learning in network MDPs
by: Ren, Zhaolin, et al.
Published: (2024)

MPCritic: A plug-and-play MPC architecture for reinforcement learning
by: Lawrence, Nathan P., et al.
Published: (2025)

Dynamic robotic cloth folding with efficient Koopman operator-based model predictive control
by: Caldarelli, Edoardo, et al.
Published: (2026)

CORL: Reinforcement Learning of MILP Policies Solved via Branch and Bound
by: Anand, Akhil S, et al.
Published: (2025)

Beacon, a lightweight deep reinforcement learning benchmark library for flow control
by: Viquerat, Jonathan, et al.
Published: (2024)

Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems
by: Ruddick, Julian, et al.
Published: (2024)

Stabilizing reinforcement learning control: A modular framework for optimizing over all stable behavior
by: Lawrence, Nathan P., et al.
Published: (2023)

Guided Safe Shooting: model based reinforcement learning with safety constraints
by: Paolo, Giuseppe, et al.
Published: (2022)

Approximate non-linear model predictive control with safety-augmented neural networks
by: Hose, Henrik, et al.
Published: (2023)

Dynamic object goal pushing with mobile manipulators through model-free constrained reinforcement learning
by: Dadiotis, Ioannis, et al.
Published: (2025)

Deep reinforcement learning-based spacecraft attitude control with pointing keep-out constraint
by: Yang, Juntang, et al.
Published: (2025)

A dual mode adaptive basal-bolus advisor based on reinforcement learning
by: Sun, Qingnan, et al.
Published: (2019)

Operator learning for energy-efficient building ventilation control with computational fluid dynamics simulation of a real-world classroom
by: Bian, Yuexin, et al.
Published: (2025)

Aerobatic maneuvers in insect-scale flapping-wing aerial robots via deep-learned robust tube model predictive control
by: Hsiao, Yi-Hsuan, et al.
Published: (2025)

Impact of data for forecasting on performance of model predictive control in buildings with smart energy storage
by: Langtry, Max, et al.
Published: (2024)

Beyond expected value: geometric mean optimization for long-term policy performance in reinforcement learning
by: Sheng, Xinyi, et al.
Published: (2025)

Independent policy gradient-based reinforcement learning for economic and reliable energy management of multi-microgrid systems
by: Hu, Junkai, et al.
Published: (2025)

Adaptive prediction theory combining offline and online learning
by: Li, Haizheng, et al.
Published: (2025)

Error whitening: Why Gauss-Newton outperforms Newton
by: McKay, Maricela Best, et al.
Published: (2026)

Improved uncertainty quantification for neural networks with Bayesian last layer
by: Fiedler, Felix, et al.
Published: (2023)

Contingency-constrained economic dispatch with safe reinforcement learning
by: Eichelbeck, Michael, et al.
Published: (2022)

PolyFormer: learning efficient reformulations for scalable optimization under complex physical constraints
by: Wen, Yilin, et al.
Published: (2026)

Orthogonal projection-based regularization for efficient model augmentation
by: Györök, Bendegúz M., et al.
Published: (2025)