This article reviews the recent development of adaptive dynamic programming (ADP) with
applications in control. First, its applications in optimal regulation are introduced, and some …

Reinforcement learning (RL) is a powerful paradigm for sequential decision-making under
uncertainties, and most RL algorithms aim to maximize some numerical value which …

This article presents a novel efficient experience-replay-based adaptive dynamic
programming (ADP) for the optimal control problem of a class of nonlinear dynamical …

This paper investigates visual navigation and control of a cooperative unmanned surface
vehicle (USV)-unmanned aerial vehicle (UAV) system for marine search and rescue. First, a …

The fault-tolerant control problem of a hydraulic servo actuator in the presence of actuator
faults is studied utilizing adaptive dynamic programming. This task is challenging because of …

The idea of optimization can be regarded as an important basis of many disciplines and
hence is extremely useful for a large number of research fields, particularly for artificial …

Optimal control problems are ubiquitous in practical engineering applications and social life
with the idea of cost or resource conservation. Based on the critic learning scheme, adaptive …

This article presents an event-triggered adaptive dynamic programming (ETADP) algorithm
to address the distributed finite-horizon consensus problem of nonlinear homogeneous …

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is
conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in …

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each
other when performing intelligent optimization. They are both regarded as promising …