Customer credit scoring is a dynamic interactive process. Simply designing the static reward
function for deep reinforcement learning may be difficult to guide an agent to adapt to the …

This paper presents an adaptive neuro-fuzzy PID controller based on twin delayed deep
deterministic policy gradient (TD3) algorithm for nonlinear systems. In this approach, the …

The movable anchor points make reconfigurable cable-driven parallel robots (RCDPRs)
advantageous over conventional cable-driven parallel robots with fixed anchor points, but …

A Cable-Driven Parallel Robot (CDPR) with Mobile Bases (MBs) can modify its geometric
architecture and is suitable for manipulation tasks in constrained environments. In …

Cable-driven parallel robots (CDPRs) use cables instead of the rigid limbs of traditional
parallel robots, thus processing a large potential workspace, easy to assemble and …

This study proposes a method based on reinforcement learning (RL) for point-to-point and
dynamic reference position tracking control of a planar cable-driven parallel robots, which is …

This article presents a literature review of the past five years of studies using Deep
Reinforcement Learning (DRL) and Inverse Reinforcement Learning (IRL) in robotic …

Although deep reinforcement learning (DRL) algorithms with experience replay have been
used to solve many sequential learning problems, applications of DRL in real-world robotics …

This paper is devoted to model‐free attitude control of rigid spacecraft in the presence of
control torque saturation and external disturbances. Specifically, a model‐free deep …

Learning to adapt and make real-time informed decisions in a dynamic and complex
environment is a challenging problem. Monopoly is a popular strategic board game that …