This article focuses on the fixed-time formation control problem for nonlinear multiagent
systems (MASs) with dynamic uncertainties and limited communication resources. Under the …

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 …

In this article, a novel reinforcement learning-based optimal tracking control (RLOTC)
scheme is established for an unmanned surface vehicle (USV) in the presence of complex …

This paper investigates the automatic exploration problem under the unknown environment,
which is the key point of applying the robotic system to some social tasks. The solution to this …

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 …

Major challenges of controlling human–robot collaboration (HRC)-oriented modular robot
manipulators (MRMs) include the estimation of human motion intention while cooperating …

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

In this article, a dynamic event-triggered control scheme for a class of stochastic nonlinear
systems with unknown input saturation and partially unmeasured states is presented. First, a …

Real-time strategy games have been an important field of game artificial intelligence in
recent years. This paper presents a reinforcement learning and curriculum transfer learning …

In this article, we consider an iterative adaptive dynamic programming (ADP) algorithm
within the Hamiltonian-driven framework to solve the Hamilton–Jacobi–Bellman (HJB) …