How to certify machine learning based safety-critical systems? A systematic literature review
Abstract Context Machine Learning (ML) has been at the heart of many innovations over the
past years. However, including it in so-called “safety-critical” systems such as automotive or …
past years. However, including it in so-called “safety-critical” systems such as automotive or …
Model-Free λ-Policy Iteration for Discrete-Time Linear Quadratic Regulation
This article presents a model-free-policy iteration (-PI) for the discrete-time linear quadratic
regulation (LQR) problem. To solve the algebraic Riccati equation arising from solving the …
regulation (LQR) problem. To solve the algebraic Riccati equation arising from solving the …
Cooperative finitely excited learning for dynamical games
In this article, we propose a way to enhance the learning framework for zero-sum games
with dynamics evolving in continuous time. In contrast to the conventional centralized actor …
with dynamics evolving in continuous time. In contrast to the conventional centralized actor …
Robust actor–critic learning for continuous-time nonlinear systems with unmodeled dynamics
This article considers the robust optimal control problem for a class of nonlinear systems in
the presence of unmodeled dynamics. An adaptive optimal controller is designed using the …
the presence of unmodeled dynamics. An adaptive optimal controller is designed using the …
Data-driven inverse reinforcement learning control for linear multiplayer games
This article proposes a data-driven inverse reinforcement learning (RL) control algorithm for
nonzero-sum multiplayer games in linear continuous-time differential dynamical systems …
nonzero-sum multiplayer games in linear continuous-time differential dynamical systems …
Adaptive fuzzy leader–follower synchronization of constrained heterogeneous multiagent systems
This article considers the distributed adaptive neuro-fuzzy output feedback control protocol
design to solve the output synchronization problem for heterogeneous multiagent systems …
design to solve the output synchronization problem for heterogeneous multiagent systems …
Safety-aware pursuit-evasion games in unknown environments using gaussian processes and finite-time convergent reinforcement learning
This article develops a safe pursuit-evasion game for enabling finite-time capture, optimal
performance as well as adaptation to an unknown cluttered environment. The pursuit …
performance as well as adaptation to an unknown cluttered environment. The pursuit …
Adaptive dynamic programming for optimal control of discrete‐time nonlinear system with state constraints based on control barrier function
Adaptive dynamic programming (ADP) methods have demonstrated their efficiency.
However, many of the applications for which ADP offers great potential, are also safety …
However, many of the applications for which ADP offers great potential, are also safety …
Online inverse reinforcement learning for nonlinear systems with adversarial attacks
In the inverse reinforcement learning (RL) problem, there are two agents. A learner agent
seeks to mimic another expert agent's state and control input behavior trajectories by …
seeks to mimic another expert agent's state and control input behavior trajectories by …
Barrier-critic adaptive robust control of nonzero-sum differential games for uncertain nonlinear systems with state constraints
C Qin, X Qiao, J Wang, D Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article, for the nonzero-sum (NZS) differential games problem of uncertain nonlinear
systems with state constraints, an adaptive robust stabilization scheme based on the control …
systems with state constraints, an adaptive robust stabilization scheme based on the control …