Cover Image

Discrete fully probabilistic design: towards a control pipeline for the synthesis of policies from examples

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ferrentino, Enrico, Chiacchio, Pasquale, Russo, Giovanni
Format:	Preprint
Published:	2021
Subjects:	Systems and Control Machine Learning Optimization and Control
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Safe haptic teleoperations of admittance controlled robots with virtualization of the force feedback
by: Pagliara, Lorenzo, et al.
Published: (2024)

SafEDMD: A Koopman-based data-driven controller design framework for nonlinear dynamical systems
by: Strässer, Robin, et al.
Published: (2024)

Counter-example guided inductive synthesis of control Lyapunov functions for uncertain systems
by: Masti, Daniele, et al.
Published: (2023)

Differentiable Discrete Event Simulation for Queuing Network Control
by: Che, Ethan, et al.
Published: (2024)

Mutual Information Optimal Control of Discrete-Time Linear Systems
by: Enami, Shoju, et al.
Published: (2025)

Tempering the Bayes Filter towards Improved Model-Based Estimation
by: van Zutphen, Menno, et al.
Published: (2025)

A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
by: Luo, Yujia, et al.
Published: (2026)

Stability and Performance Analysis of Discrete-Time ReLU Recurrent Neural Networks
by: Noori, Sahel Vahedi, et al.
Published: (2024)

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

Discrete-time Contraction-based Control of Nonlinear Systems with Parametric Uncertainties using Neural Networks
by: Wei, Lai, et al.
Published: (2021)

Regret Analysis: a control perspective
by: Gibson, Travis E., 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)

Revealing design archetypes and flexibility in e-molecule import pathways using Modeling to Generate Alternatives and interpretable machine learning
by: Kchaou, Mahdi, et al.
Published: (2025)

Risk-sensitive control as inference with Rényi divergence
by: Ito, Kaito, et al.
Published: (2024)

What price to pay? Auto-tuning a building MPC controller for optimal economic cost
by: Yu, Jiarui, et al.
Published: (2025)

Reliably-stabilizing piecewise-affine neural network controllers
by: Fabiani, Filippo, et al.
Published: (2021)

A minimax optimal control approach for robust neural ODEs
by: Cipriani, Cristina, et al.
Published: (2023)

From NeurODEs to AutoencODEs: a mean-field control framework for width-varying Neural Networks
by: Cipriani, Cristina, et al.
Published: (2023)

Safe and Robust Domains of Attraction for Discrete-Time Systems: A Set-Based Characterization and Certifiable Neural Network Estimation
by: Serry, Mohamed, et al.
Published: (2026)

A neural network-based approach to hybrid systems identification for control
by: Fabiani, Filippo, et al.
Published: (2024)

Safe learning-based control via function-based uncertainty quantification
by: Tokmak, Abdullah, et al.
Published: (2026)

Towards safe control parameter tuning in distributed multi-agent systems
by: Tokmak, Abdullah, et al.
Published: (2025)

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

Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method
by: Caldarelli, Edoardo, et al.
Published: (2024)

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

A least-square method for non-asymptotic identification in linear switching control
by: Sun, Haoyuan, et al.
Published: (2024)

Compositional Diffusion Models for Powered Descent Trajectory Generation with Flexible Constraints
by: Briden, Julia, et al.
Published: (2024)

Human-Robot Interface for Teleoperated Robotized Planetary Sample Collection and Assembly
by: Pagliara, Lorenzo, et al.
Published: (2024)

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

End-to-end guarantees for indirect data-driven control of bilinear systems with finite stochastic data
by: Chatzikiriakos, Nicolas, et al.
Published: (2024)

Discretized Distributed Optimization over Dynamic Digraphs
by: Doostmohammadian, Mohammadreza, et al.
Published: (2023)

Smart energy management: process structure-based hybrid neural networks for optimal scheduling and economic predictive control in integrated systems
by: Wu, Long, et al.
Published: (2024)

Optimal Low Emission Zones scheduling as an example of transport policy backcasting
by: Alami, Asmae, et al.
Published: (2025)

An active learning method for solving competitive multi-agent decision-making and control problems
by: Fabiani, Filippo, et al.
Published: (2022)

On the Stability Connection Between Discrete-Time Algorithms and Their Resolution ODEs: Applications to Min-Max Optimisation
by: Farzin, Amir Ali, et al.
Published: (2026)

Learning Linear Dynamics from Bilinear Observations
by: Sattar, Yahya, et al.
Published: (2024)

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

Online Residual Learning from Offline Experts for Pedestrian Tracking
by: Vlachos, Anastasios, et al.
Published: (2024)

Symmetric Linear Dynamical Systems are Learnable from Few Observations
by: Vu, Minh, et al.
Published: (2025)

Towards a Systems Theory of Algorithms
by: Dörfler, Florian, et al.
Published: (2024)