Off‐policy model‐based end‐to‐end safe reinforcement learning
From MaRDI portal
Publication:6117696
DOI10.1002/rnc.7109OpenAlexW4388852236MaRDI QIDQ6117696
Unnamed Author, Unnamed Author, Didier Theilliol
Publication date: 20 March 2024
Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/rnc.7109
Learning and adaptive systems in artificial intelligence (68T05) Lyapunov and storage functions (93D30) Input-output approaches in control theory (93D25)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Computational adaptive optimal control for continuous-time linear systems with completely unknown dynamics
- Barrier function based model predictive control
- Model-free \(Q\)-learning designs for linear discrete-time zero-sum games with application to \(H^\infty\) control
- Robust control barrier functions for constrained stabilization of nonlinear systems
- Safe exploration in model-based reinforcement learning using control barrier functions
- Distributed Coordination Control for Multi-Robot Networks Using Lyapunov-Like Barrier Functions
- A Learning Algorithm for Risk-Sensitive Cost
- An Approximation Theory of Optimal Control for Trainable Manipulators
- Inverse optimal design of input-to-state stabilizing nonlinear controllers
- Control Barrier Function Based Quadratic Programs for Safety Critical Systems
- Safe reinforcement learning for dynamical games
- A time-dependent Hamilton-Jacobi formulation of reachable sets for continuous dynamic games
- Reinforcement Learning and Feedback Control: Using Natural Decision Methods to Design Optimal Adaptive Controllers
- Safe reinforcement learning: A control barrier function optimization approach
This page was built for publication: Off‐policy model‐based end‐to‐end safe reinforcement learning