Inverse optimal control (IOC) is an advanced methodological framework that seeks to deduce the underlying cost or reward functions based solely on the observation of optimal behaviour. Traditionally, ...

Abstract: In this paper, a new data-based Q-learning algorithm is proposed to address the optimal control issue for a class of discrete-time switched affine systems (SASs). The algorithm shifts the ...

Abstract: This paper addresses the constrained infinite-horizon optimal control problem for autonomous vehicles operating in avoidance regions. A novel online adaptive safe reinforcement learning (RL) ...

Model Predictive Control (MPC) is a modern feedback law that generates the control signal by solving an optimal control problem at each sampling time. This approach is capable of maximizing a certain ...

This paper describes an application of dynamic programming to determining optimal driver control of an automobile for fuel economy. The objective function is provided by a simulator that uses vehicle ...